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SPIRES-BOOKS: FIND KEYWORD PATTERN RECOGNITION *END*INIT* use /tmp/qspiwww.webspi1/23964.36 QRY 131.225.70.96 . find keyword pattern recognition ( in books using www Cover
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Call number:1118999738:ONLINE Show nearby items on shelf
Title:Error Estimation for Pattern Recognition
Author(s): Braga-Neto
Date:2015
Publisher:Wiley-IEEE Press
Size:1 online resource (337 p.)
ISBN:9781118999738
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:1118893689:ONLINE Show nearby items on shelf
Title:Pattern Recognition in Computational Molecular Biology: Techniques and Approaches
Author(s): Elloumi
Date:2015
Publisher:Wiley
Size:1 online resource (657 p.)
ISBN:9781118893685
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:1118130669:ONLINE Show nearby items on shelf
Title:Emotion Recognition: A Pattern Analysis Approach
Author(s): Konar
Date:2015
Publisher:Wiley
Size:1 online resource (585 p.)
ISBN:9781118130667
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:111800440X:ONLINE Show nearby items on shelf
Title:Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging
Author(s): Maji
Date:2012
Publisher:Wiley-IEEE Computer Society Pr
Size:1 online resource (313 p.)
ISBN:9781118004401
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:0471741086:ONLINE Show nearby items on shelf
Title:A Statistical Approach to Neural Networks for Pattern Recognition
Author(s): Dunne
Date:2007
Publisher:Wiley-Interscience
Size:1 online resource (289 p.)
ISBN:9780471741084
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0471615315:ONLINE Show nearby items on shelf
Title:Discriminant Analysis and Statistical Pattern Recognition
Author(s): McLachlan
Date:1992
Publisher:Wiley-Interscience
Size:1 online resource (527 p.)
ISBN:9780471615316
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0471221767:ONLINE Show nearby items on shelf
Title:Random Graphs for Statistical Pattern Recognition
Author(s): Marchette
Date:2004
Publisher:Wiley-Interscience
Size:1 online resource (238 p.)
ISBN:9780471221760
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470845139:ONLINE Show nearby items on shelf
Title:Statistical Pattern Recognition 2e
Author(s): Webb
Date:2002
Publisher:Wiley
Size:1 online resource (515 p.)
ISBN:9780470845134
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470699876:ONLINE Show nearby items on shelf
Title:Moments and Moment Invariants in Pattern Recognition
Author(s): Flusser
Date:2009
Publisher:Wiley
Size:1 online resource (313 p.)
ISBN:9780470699874
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:0470682280:ONLINE Show nearby items on shelf
Title:Statistical Pattern Recognition 3e
Author(s): Webb
Date:2011
Publisher:Wiley
Size:1 online resource (667 p.)
ISBN:9780470682289
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470404612:ONLINE Show nearby items on shelf
Title:Image Processing and Pattern Recognition: Fundamentals and Techniques
Author(s): Shih
Date:2010
Publisher:Wiley-IEEE Press
Size:1 online resource (553 p.)
ISBN:9780470404614
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Electrical & Electronics Engineering
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Call number:TK7895.O6UL4 Show nearby items on shelf
Title:Pattern recognition techniques
Author(s): Julian Richard Ullmann 1936-
Date:1973
Publisher:Crane, Russak, New York
Size:412
ISBN:0844801739
Keywords: Optical pattern recognition.
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Call number:SPRINGER-2016-9783319305158:ONLINE Show nearby items on shelf
Title:Search Techniques in Intelligent Classification Systems
Author(s): Andrey V Savchenko
Date:2016
Size:1 online resource (19 p.)
Note:10.1007/978-3-319-30515-8
Contents:1.Intelligent Classification Systems -- 2. Statistical Classification of Audiovisual Data -- 3. Hierarchical Intelligent Classification Systems -- 4. Approximate Nearest Neighbor Search in Intelligent Classification Systems -- 5. Search in Voice Co ntrol Systems -- 6. Conclusion.
ISBN:9783319305158
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Pattern recognition , Potential theory (Mathematics) , System theory , Mathematical optimization , Machinery , Mathematics , Optimization , Pattern Recognition , Machinery and Machine Elements , Systems Theory, Control , Complex Systems , Potential Theory
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Call number:SPRINGER-2016-9783319300306:ONLINE Show nearby items on shelf
Title:Computing Characterizations of Drugs for Ion Channels and Receptors Using Markov Models
Author(s): Aslak Tveito
Date:2016
Size:1 online resource (30 p.)
Note:10.1007/978-3-319-30030-6
Contents:Preface -- Background: Contents and Method -- One-dimensional calcium release -- Models of open and state blockers -- Two-dimensional calcium release -- Computing theoretical drugs in the two-dimensional case -- Generalized systems -- Calcium-induc ed calcium release -- Numerical release for CICR -- A prototypical model of an ion channel -- Inactivated ion channels -- A simple model of the sodium channel -- Mutations affecting the mean open time -- The burst mode -- Whole sale action potentials --
ISBN:9783319300306
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Lecture Notes in Computational Science and Engineering: 111
Keywords: Mathematics , Computer graphics , Computer mathematics , Mathematics , Computational Science and Engineering , Biomedicine general , Computer Imaging, Vision, Pattern Recognition and Graphics
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Call number:SPRINGER-2014-9783319040998:ONLINE Show nearby items on shelf
Title:Topological Methods in Data Analysis and Visualization III [electronic resource] : Theory, Algorithms, and Applications
Author(s): Peer-Timo Bremer
Ingrid Hotz
Valerio Pascucci
Ronald Peikert
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:This collection of peer-reviewed conference papers provides comprehensive coverage of cutting-edge research in topological approaches to data analysis and visualization. It encompasses the full range of new algorithms andinsights, including fast homo logy computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The volume also features material on core research challenges such as therepresentation of large and complex datasets and integrati ng numerical methods with robust combinatorial algorithms. Reflecting the focus of the TopoInVis 2013 conference, the contributions evince the progress currently being made onfinding experimental solutions to open problems in the sector. They provide an i nclusive snapshot of state-of-the-art research that enables researchers to keep abreast of the latest developments and provides a foundation for futureprogress. With papers by some of the worlds leading experts in topological techniques, this volume is a major contribution to the literature in a field of growing importance with applications in disciplines that range fromengineering to medicine
Contents:Part I Robust Topological Analysis: 1 Robust Detection of Singularities in Vector Fields: H. Bhatia, A. Gyulassy, H. Wang, P
T. Bremer and V. Pascucci
2 Interpreting Feature Tracking Through the Lens of Robustness: P. Skraba and B. Wang
3 Simplification of Morse Decompositions using Morse Set Mergers: L. Sipeki and A. Szymczak
4 Toward the Extraction of Saddle Periodic Orbits: J. Kasten, J. Reininghaus, W. Reich and G. Scheuermann
Part II Efficient Computation of Topology
5 Computational Topology via Functional Programming: A Baseline Analysis: D. Duke and H. Carr
6 Distribu
ISBN:9783319040998
Series:eBooks
Series:SpringerLink
Series:Mathematics and Visualization, 1612-3786
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer vision , Optical pattern recognition , Global analysis (Mathematics) , Visualization , Geometry , Topology
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Call number:SPRINGER-2014-9783319024752:ONLINE Show nearby items on shelf
Title:Computational Diffusion MRI and Brain Connectivity [electronic resource] : MICCAI Workshops, Nagoya, Japan, September 22nd, 2013
Author(s): Thomas Schultz
Gemma Nedjati-Gilani
Archana Venkataraman
Lauren O'Donnell
Eleftheria Panagiotaki
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:This volume contains the proceedings from two closely related workshops: Computational Diffusion MRI (CDMRI13) and Mathematical Methods from Brain Connectivity (MMBC13), held under the auspices of the 16th InternationalConference on Medical Image Com puting and Computer Assisted Intervention, which took place in Nagoya, Japan, September 2013. Inside, readers will find contributions ranging from mathematical foundations and novel methods for thevalidation of inferring large-scale connectivity from neur oimaging data to the statistical analysis of the data, accelerated methods for data acquisition, and the most recent developments on mathematical diffusion modeling. This volumeoffers a valuable starting point for anyone interested in learning computation al diffusion MRI and mathematical methods for brain connectivity as well as offers new perspectives and insights on current research challenges for thosecurrently in the field. It will be of interest to researchers and practitioners in computer science, M R physics, and applied mathematics
Contents:Part I Acquisition of Diffusion MRI: Comparing Simultaneous Multi
slice Diffusion Acquisitions by Y.Rathi et al
Effect of Data Acquisition and Analysis Method on Fiber Orientation Estimation in Diffusion MRI by B.Wilkins et al
Model
based super
resolution of diffusion MRI by A.Tobisch et al
A quantitative evaluation of errors induced by reduced field
of
view in diffusion tensor imaging by J.Hering et al
Part II Diffusion MRI Modeling: The Diffusion Dictionary in the Human Brain is Short: Rotation Invariant Learning of Basis Functions by M.Reisert et al
Diffusion Propagator Estim
ISBN:9783319024752
Series:eBooks
Series:SpringerLink
Series:Mathematics and Visualization, 1612-3786
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer vision , Optical pattern recognition , Computer science , Visualization , Statistics
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Call number:SPRINGER-2013-9781461482864:ONLINE Show nearby items on shelf
Title:Estimation and Control Problems for Stochastic Partial Differential Equations [electronic resource]
Author(s): Pavel S Knopov
Olena N Deriyeva
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Focusing on research surrounding aspects of insufficiently studied problems of estimation and optimal control of random fields, this book exposes some important aspects of those fields for systems modeled by stochastic partialdifferential equations. It contains many results of interest to specialists in both the theory of random fields and optimal control theory who use modern mathematical tools for resolving specific applied problems, and presents researchthat has not previously been covered. More g enerally, this book is intended for scientists, graduate, and post-graduates specializing in probability theory and mathematical statistics. The models presented describe many processes inturbulence theory, fluid mechanics, hydrology, astronomy, and meteo rology, and are widely used in pattern recognition theory and parameter identification of stochastic systems. Therefore, this book may also be useful to appliedmathematicians who use probability and statistical methods in the selection of useful signals s ubject to noise, hypothesis distinguishing, distributed parameter systems optimal control, and more. Material presented in this monographcan be used for education courses on the estimation and control theory of random fields
Note:Springer eBooks
Contents:1. Two Parameter Martingales and Their Properties
2. Stochastic Differential Equations on the Plane
3. Filtration and Prediction Problems for Stochastic Fields
4. Control Problem for Diffusion
Type Random Fields
5. Stochastic Processes in a Hilbert Space
References
ISBN:9781461482864
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Optimization and Its Applications, 1931-6828 : v83
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Differential equations, partial , Systems theory , Mathematical optimization
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Call number:SPRINGER-2013-9781461450764:ONLINE Show nearby items on shelf
Title:Mathematical Methodologies in Pattern Recognition and Machine Learning [electronic resource] : Contributions from the International Conference on Pattern Recognition Applications and Methods, 2012
Author(s): Pedro Latorre Carmona
J. Salvador Snchez
Ana L.N Fred
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Springer eBooks
ISBN:9781461450764
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Proceedings in Mathematics & Statistics, 2194-1009 : v30
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer science , Optical pattern recognition , Systems theory , Mathematical optimization
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Call number:SPRINGER-2012-9783642290756:ONLINE Show nearby items on shelf
Title:Novelty, Information and Surprise [electronic resource]
Author(s): Gnther Palm
Date:2012
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The book offers a new approach to information theory that is more general then the classical approach by Shannon. The classical definition of information is given for an alphabet of symbols or for a set of mutually exclusivepropositions (a partition of the probability space ) with corresponding probabilities adding up to 1. The new definition is given for an arbitrary cover of , i.e. for a set of possibly overlapping propositions. The generalizedinformation concept is called novelty and it is accompa nied by two new concepts derived from it, designated as information and surprise, which describe opposite versions of novelty, information being related more to classicalinformation theory and surprise being related more to the classical concept of statis tical significance. In the discussion of these three concepts and their interrelations several properties or classes of covers are defined, which turnout to be lattices. The book also presents applications of these new concepts, mostly in statistics and i n neuroscience
Note:Springer eBooks
Contents:Part I Surprise and Information of Descriptions: Prerequisites
Improbability and Novelty of Descriptions
Conditional Novelty and Information
Part II Coding and Information Transmission: On Guessing and Coding
Information Transmission
Part III Information Rate and Channel Capacity: Stationary Processes and Information Rate
Channel Capacity
Shannon's Theorem
Part IV Repertoires and Covers: Repertoires and Descriptions
Novelty, Information and Surprise of Repertoires
Conditioning, Mutual Information and Information Gain
Part V Information, Novelty and Surprise in
ISBN:9783642290756
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Artificial intelligence , Optical pattern recognition , Neurobiology , Algebra
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Call number:SPRINGER-2012-9781461442110:ONLINE Show nearby items on shelf
Title:Methods of Optimization and Systems Analysis for Problems of Transcomputational Complexity [electronic resource]
Author(s): Ivan V Sergienko
Date:2012
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This work presents lines of investigation and scientific achievements of the Ukrainian school of optimization theory and adjacent disciplines. These include the development ofapproaches to mathematical theories, methodologies,methods, and application systems for the solution of applied problems in economy, finances, energy saving, agriculture, biology, genetics, environmental protection, hardware and software engineering, information protection, decisionmaking, pattern recognition, self-adapting cont rol of complicated objects, personnel training, etc. The methods developed include sequential analysis of variants, nondifferential optimization, stochastic optimization, discreteoptimization, mathematical modeling, econometric modeling, solution of extre mum problems on graphs, construction of discrete images and combinatorial recognition, etc. Some of these methods became well known in the world's mathematicalcommunity and are now known as classic methods
Note:Springer eBooks
Contents:Preface
1. Science Was the Meaning of His Life
2. Optimization Methods and Their Efficient Use
3.Mathematical Modeling and Analysis of Complex Processes on Supercomputer Systems
4. Problems of Modeling and Analysis of Processes in Economic Cybernetics
5. Problems of Solving Complicated Combinatorial Problems
Afterward
References
Index
ISBN:9781461442110
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Optimization and Its Applications, 1931-6828 : v72
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer simulation , Computer vision , Mathematical optimization
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Call number:SPRINGER-2012-9781461432463:ONLINE Show nearby items on shelf
Title:One-Shot Color Astronomical Imaging [electronic resource]
Author(s): L. A. Kennedy
Date:2012
Publisher:Springer US
Size:1 online resource
Note:Popular science
Note:Springer 2012 Physics and Astronomy eBook collection
Note:Springer e-book platform
ISBN:9781461432463
Series:Practical Astronomy
Series:e-books
Keywords: Astronomy, Observations and Techniques , Popular Science in Astronomy , Computer Imaging, Vision, Pattern Recognition and Graphics
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Call number:SPRINGER-2012-9781461420224:ONLINE Show nearby items on shelf
Title:Theory, Analysis and Design of RF Interferometric Sensors [electronic resource]
Author(s): Cam Nguyen
Seoktae Kim
Date:2012
Edition:1
Publisher:Springer New York
Size:1 online resource
Note:Brief
Note:Springer 2012 Physics and Astronomy eBook collection
Note:Springer e-book platform
ISBN:9781461420224
Series:SpringerBriefs in Physics
Series:e-books
Keywords: Microwaves, RF and Optical Engineering , Optics, Optoelectronics, Plasmonics and Optical Devices , Computer Imaging, Vision, Pattern Recognition and Graphics , Circuits and Systems , Applied and Technical Physics
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Call number:SPRINGER-2011-9783642158162:ONLINE Show nearby items on shelf
Title:Biomedical Image Processing [electronic resource]
Author(s): Thomas Martin Deserno
Date:2011
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become animportant option for he alth care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlightingrecent advances that have been made in academ ics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics
Note:Springer eBooks
Contents:Fundamentals of Biomedical Image Processing
Part I: Image Formation
Fusion of PET and MRI for Hybrid Imaging
Cardiac 4D Ultrasound Imaging
Part II: Image Enhancement
Morphological Image Processing Applied in Biomedicine
Medical Image Registration
Part III: Feature Extraction and Selection
Multi
Scale and Multi
Orientation Medical Image Analysis
Feature Extraction and Selection for Decision Making
Part IV: Segmentation
Parametric and Non
Parametric Clustering for Segmentation
Region
Based Segmentation: Fuzzy Connectedness, Graph Cut and Related Algorithms
ISBN:9783642158162
Series:e-books
Series:SpringerLink (Online service)
Series:Biological and Medical Physics, Biomedical Engineering, 1618-7210
Series:Physics and Astronomy (Springer-11651)
Keywords: Medicine , Radiology, Medical , Computer vision , Optical pattern recognition
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Call number:SPRINGER-2011-9780857297488:ONLINE Show nearby items on shelf
Title:Computer Vision Using Local Binary Patterns [electronic resource]
Author(s): Matti Pietikinen
Abdenour Hadid
Guoying Zhao
Timo Ahonen
Date:2011
Publisher:London : Springer London : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3Dtextures and spatiote mporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have providedoutstanding results in problems relating t o face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patternsprovides a detailed description of the LBP methods and their varian ts both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solvingdifferent kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: - Local binary patterns and their variants in spatial and spatiotemporal domains - Texture classification and s egmentation, description of interest regions - Applications in image retrieval and 3D recognition - Recognition andsegmentation of dynamic textures - Background subtraction, recognition of actions - Face analysis using still images and image sequences, vi sual speech recognition - LBP in various applications Written by pioneers of LBP, this bookis an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will al so be of interest to all those who work with specific applications ofmachine vision
Note:Springer eBooks
Contents:Background
Local binary patterns for still images
Spatiotemporal LBP
Texture classification and segmentation
Description of interest regions
Applications in image retrieval and 3D recognition
Recognition and segmentation of dynamic textures
Background subtraction
Recognition of actions
Face analysis using still images
Face analysis using image sequences
Visual recognition of spoken phrases
LBP in different applications
ISBN:9780857297488
Series:e-books
Series:SpringerLink (Online service)
Series:Computational Imaging and Vision, 1381-6446 : v40
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer vision , Optical pattern recognition , Biometrics
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Call number:SPRINGER-2010-9783642001895:ONLINE Show nearby items on shelf
Title:On the Construction of Artificial Brains [electronic resource]
Author(s): Ulrich Ramacher
Christoph Malsburg
Date:2010
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book presents a first generation of artificial brains, using vision as sample application. An object recognition system is built, using neurons and synapses as exclusive building elements. The system contains a featurepyramid with 8 orientations and 5 resolution levels for 1000 objects and networks for binding of features into objects. This vision system can recognize objects robustly in the presence of changes in illumination, deformation, distanceand pose (as long as object components remain v isible). The neuro-synaptic network owes its functional power to the introduction of rapidly modifiable dynamic synapses. These give a network greater pattern recognition capabilities thanare achievable with fixed connections. The spatio-temporal correlat ion structure of patterns is captured by a single synaptic differential equation in a universal way. The correlation can appear as synchronous neural firing, whichsignals the presence of a feature in a robust way, or binds features into objects. Although in this book we can present only a first generation artificial brain and believe many more generations will have to follow to reach the fullpower of the human brain, we nevertheless see a new era of computation on the horizon. There were times when comput ers, with their precision, reliability and blinding speed, were considered to be as superior to the wet matter of ourbrain as a jet plane is to a sparrow. These times seem to be over, given the fact that digital systems inspired by formal logic and contro lled algorithmically - today's computers - are hitting a complexity crisis. A paradigm change isin the air: from the externally organised to the self-organised computer, of which the results described in this book may give an inkling
Note:Springer eBooks
Contents:The Difficulty of Modelling Artificial Brains
Information Processing In Nets with Constant Synapses
Theory of Nets with Constant or Dynamic Synapses
Macro
Dynamics of Nets with Constant Synapses
Information Processing with Dynamic Synapses
Nets for Feature Detection
Nets for Feature Recognition
Nets for Robust Head Detection
Extensions of The Vision Architecture
Look
Out
Preliminary Considerations on The Microelectronic Implementation
Elementary Circuits for Neurons, Synapses, and Photosensors
Simulation of Microelectronic Neural Circuits and Systems
Arch
ISBN:9783642001895
Series:e-books
Series:SpringerLink (Online service)
Series:Physics and Astronomy (Springer-11651)
Keywords: Neurosciences , Artificial intelligence , Vibration , Electronics
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Call number:SPRINGER-2009-9783540878339:ONLINE Show nearby items on shelf
Title:Structure in Complex Networks [electronic resource]
Author(s): J Reichardt
Date:2009
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:In the modern world of gigantic datasets, which scientists and practioners of all fields of learning are confronted with, the availability of robust, scalable and easy-to-use methods for pattern recognition and data mining are ofparamount importance, so as to be able to cope with the avalanche of data in a meaningful way. This concise and pedagogical research monograph introduces the reader to two specific aspects - clustering techniques and dimensionalityreduction - in the context of complex network analysis. The first chapter provides a short introduction into relevant graph theoretical notation chapter 2 then reviews and compares a number of cluster definitions from different fieldsof science. In the subsequent chapters, a first-principles approac h to graph clustering in complex networks is developed using methods from statistical physics and the reader will learn, that even today, this field significantlycontributes to the understanding and resolution of the related statistical inference issues. Finally, an application chapter examines real-world networks from the economic realm to show how the network clustering process can be used todeal with large, sparse datasets where conventional analyses fail
Note:Springer eBooks
Contents:to Complex Networks
Standard Approaches to Network Structure: Block Modeling
A First Principles Approach to Block Structure Detection
Diagonal Block Models as Cohesive Groups
Modularity of Dense Random Graphs
Modularity of Sparse Random Graphs
Applications
Conclusion and Outlook
ISBN:9783540878339
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Physics, 0075-8450 : v766
Series:Physics and Astronomy (Springer-11651)
Keywords: Statistical physics , Engineering , Economics , Economics, Mathematical
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Call number:SPRINGER-2009-9781402092534:ONLINE Show nearby items on shelf
Title:Unexploded Ordnance Detection and Mitigation [electronic resource]
Author(s): Jim Byrnes
Date:2009
Publisher:Dordrecht : Springer Netherlands
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The detection and neutralization of unexploded ordnance (UXO) has been of major concern for very many decades at least since the First World War. UXO continues to be the subject of intensive research in many fields of science.While today's headlines emphasize the mayhem resulting from the placement of improvised explosive devices (IEDs), humanitarian landmine clearing continues to draw significant global attention as well. In many countries of the world,landmines threaten the population and hinder re construction and fast, efficient utilization of large areas of the mined land in the aftermath of military conflicts. The reports in this volume, written by world leaders from academia,Government and industry, describe how basic ideas from mathematics, ra dar, sonar and chemistry can be combined with ongoing improvements in hardware and computation, as well as very new advances in multisensor data fusion, to yield thepromise of more sophisticated and accurate UXO detection and identification capabilities t han currently exist
Note:Springer eBooks
Contents:Wavelet Decomposition of Measures: Application to Multifractal Analysis of Images
Knowledge Based Diversity Processing
Volatile Compounds Detection by IR Acousto
optic Detectors
Ground Penetrating Radar for Buried Landmine and IED Detection
Overview of Statistical Tests for Unexploded Ordnance Detection
Low Frequency Radar for Buried Target Detection
UXO Signal Multi Sensor Detection and Estimation
Advanced Multifunctional Sensor Systems
Some Aspects of Environmental Interactions Related to UXO
Applications of Luminescence to Fingerprints and Trace Explosives Detection
ISBN:9781402092534
Series:e-books
Series:SpringerLink (Online service)
Series:NATO Science for Peace and Security Series B: Physics and Biophysics, 1874-6500
Series:Physics and Astronomy (Springer-11651)
Keywords: Geography , Analytical biochemistry , Remote sensing , Optical pattern recognition , Computer science , Microwaves
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Call number:SPRINGER-2009-9780387981352:ONLINE Show nearby items on shelf
Title:Principles and Theory for Data Mining and Machine Learning [electronic resource]
Author(s): Bertrand Clarke
Ernest Fokoue
Hao Helen Zhang
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book is a thorough introduction to the most important topics in data mining and machine learning. It begins with a detailed review of classical function estimation and proceeds with chapters on nonlinear regression,classification, and ensemble m ethods. The final chapters focus on clustering, dimension reduction, variable selection, and multiple comparisons. All these topics have undergone extraordinarily rapid development in recent years and thistreatment offers a modern perspective emphasizing the most recent contributions. The presentation of foundational results is detailed and includes many accessible proofs not readily available outside original sources. While theorientation is conceptual and theoretical, the main points are regularly reinf orced by computational comparisons. Intended primarily as a graduate level textbook for statistics, computer science, and electrical engineering students,this book assumes only a strong foundation in undergraduate statistics and mathematics, and facility with using R packages. The text has a wide variety of problems, many of an exploratory nature. There are numerous computed examples,complete with code, so that further computations can be carried out readily. The book also serves as a handbook for researc hers who want a conceptual overview of the central topics in data mining and machine learning. Bertrand Clarkeis a Professor of Statistics in the Department of Medicine, Department of Epidemiology and Public Health, and the Center for Computational Scienc es at the University of Miami. He has been on the Editorial Board of the Journal of theAmerican Statistical Association, the Journal of Statistical Planning and Inference, and Statistical Papers. He is co-winner, with Andrew Barron, of the 1990 Browder J. Thompson Prize from the Institute of Electrical and ElectronicEngineers. Ernest Fokoue is an Assistant Professor of Statistics at Kettering University. He has also taught at Ohio State University and b
Note:Springer eBooks
Contents:Variability, information, prediction
Kernel smoothing
Spline smoothing
New wave nonparametrics
Supervised learning: Partition methods
Alternative nonparametrics
Computational comparisons
Unsupervised learning: Clustering
Learning in high dimensions
Variable selection
Multiple testing
ISBN:9780387981352
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Data mining , Optical pattern recognition , Bioinformatics , Mathematical statistics
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Call number:SPRINGER-2009-9780387790527:ONLINE Show nearby items on shelf
Title:Introduction to Nonparametric Estimation [electronic resource]
Author(s): Alexandre B Tsybakov
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Methods of nonparametric estimation are located at the core of modern statistical science. The aim of this book is to give a short but mathematically self-contained introduction to the theory of nonparametric estimation. Theemphasis is on the constru ction of optimal estimators therefore the concepts of minimax optimality and adaptivity, as well as the oracle approach, occupy the central place in the book. This is a concise text developed from lecturenotes and ready to be used for a course on the grad uate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore, the results arenot always given in the most general form but rather under assumptions that lead to shorter or more elegant proofs. The book has three chapters. Chapter 1 presents basic nonparametric regression and density estimators and analyzestheir properties. Chapter 2 is devoted to a detailed treatment of minimax lower bounds. Chapter 3 develops more advanced topics: Pinsker's theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity
Note:Springer eBooks
Contents:Nonparametric estimators
Lower bounds on the minimax risk
Asymptotic efficiency and adaptation
Appendix
References
Index
ISBN:9780387790527
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Optical pattern recognition , Distribution (Probability theory) , Mathematical statistics , Econometrics
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Call number:SPRINGER-2009-9780387686288:ONLINE Show nearby items on shelf
Title:Parallel Coordinates [electronic resource] : Visual Multidimensional Geometry and Its Applications
Author(s): Alfred Inselberg
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book is about visualization, systematically incorporating the fantastic human pattern recognition into the problem-solving process, and focusing on parallel coordinates. The barrier, imposed by our three-dimensionalhabitation and perceptual expe rience, has been breached by this innovative and versatile methodology. The accurate visualization of multidimensional problems and multivariate data unlocks insights into the role of dimensionality.Beginning with an introductory chapter on geometry, the mathematical foundations are intuitively developed, interlaced with applications to data mining, information visualization, computer vision, geometric modeling, collisionavoidance for air traffic and process-control. Many results appear for the first time . Multidimensional lines, planes, proximities, surfaces and their properties are unambiguously recognized (i.e. convexity viewed in any dimension)enabling powerful construction algorithms (for intersections, interior-points, linear-programming). Key featu res of Parallel Coordinates: * An easy-to-read self-contained chapter on data mining and information visualization * Numerousexercises with solutions, from basic to advanced topics, course projects and research directions * Fast Track markers throughout p rovide a quick grasp of essential material. * Extensive bibliography, index, and a chapter containinga collection of recent results (i.e. visualizing large networks, complex-valued functions and more) Parallel Coordinates requires only an elementary knowl edge of linear algebra. It is well-suited for self-study and as a textbook (orcompanion) for courses on information visualization, data mining, mathematics, statistics, computer science, engineering, finance, management, manufacturing, in scientific disci plines and even the arts
Note:Springer eBooks
Contents:Foreword
Preface
Introduction
Geometry Background
The Plane with Parallel Coordinates
Multidimensional Lines
Hyperplanes and p
Flats RN
Envelopes
Curves
Proximity of Lines, Planes, and Flats
Hypersurfaces in RN
Data Mining and Other Applications
Recent Results
Solutions to Selected Exercises
Notation and List of Symbols
Bibliography
Index
ISBN:9780387686288
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Data mining , Computer vision , Visualization , Geometry , Mathematical optimization
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Call number:SPRINGER-2008-9783540752387:ONLINE Show nearby items on shelf
Title:Brain Dynamics [electronic resource] : An Introduction to Models and Simualtions
Author(s): Hermann Haken
Date:2008
Edition:2
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Brain Dynamics serves to introduce graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences. Some of the advanced chapters will also be of interest to thespecialists. The book approach es the subject through pulse-coupled neural networks, with at their core the lighthouse and integrate-and-fire models, which allow for the highly flexible modelling of realistic synaptic activity,synchronization and spatio-temporal pattern formation. Topi cs also include pulse-averaged equations and their application to movement coordination. The book closes with a short analysis of models versus the real neurophysiologicalsystem. The second edition has been thoroughly updated and augmented by two extensiv e chapters that discuss the interplay between pattern recognition and synchronization. Further, to enhance the usefulness as textbook and forself-study, the detailed solutions for all 34 exercises throughout the text have been added
Note:Springer eBooks
Contents:Basic Experimental Facts and Theoretical Tools
The Neuron Building Block of the Brain
Neuronal Cooperativity
Spikes, Phases, Noise: How to Describe Them Mathematically? We Learn a Few Tricks and Some Important Concepts
Spiking in Neural Nets
The Lighthouse Model. Two Coupled Neurons
The Lighthouse Model. Many Coupled Neurons
Integrate and Fire Models (IFM)
Many Neurons, General Case, Connection with Integrate and Fire Model
Pattern Recognition Versus Synchronization: Pattern Recognition
Pattern Recognition Versus Synchronization: Synchronization and Phase Lock
ISBN:9783540752387
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Synergetics, 0172-7389
Series:Physics and Astronomy (Springer-11651)
Keywords: Neurosciences , Artificial intelligence , Mathematics , Biomedical engineering , Engineering
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Call number:SPRINGER-2008-9780387781891:ONLINE Show nearby items on shelf
Title:Modern Multivariate Statistical Techniques [electronic resource] : Regression, Classification, and Manifold Learning
Author(s): Alan J Izenman
Date:2008
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the HumanGenome Project has op ened up the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The authortakes a broad perspective for the first time i n a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multipleregression, principal components, canonical variates, linear discrimina nt analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit,neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, bo osting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another uniquefeature of this book is the discussion of database management systems. This book is appropriate for advanced undergradu ate students, graduate students, and researchers in statistics, computer science, artificial intelligence,psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and pro bability and statistics is required. The book presents a carefully-integrated mixtureof theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as e xamples in the book, over 200 exercises, and many colorillustrations and photographs. Alan J. Izenman is Professor of Statistics and Director of the Center for Statistical and Information Science at Te
Note:Springer eBooks
Contents:and Preview
Data and Databases
Random Vectors and Matrices
Nonparametric Density Estimation
Model Assessment and Selection in Multiple Regression
Multivariate Regression
Linear Dimensionality Reduction
Linear Discriminant Analysis
Recursive Partitioning and Tree
Based Methods
Artificial Neural Networks
Support Vector Machines
Cluster Analysis
Multidimensional Scaling and Distance Geometry
Committee Machines
Latent Variable Models for Blind Source Separation
Nonlinear Dimensionality Reduction and Manifold Learning
Correspondence Analysis
ISBN:9780387781891
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Texts in Statistics, 1431-875X
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Data mining , Optical pattern recognition , Bioinformatics , Mathematical statistics
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Call number:SPRINGER-2008-9780387718873:ONLINE Show nearby items on shelf
Title:Information Criteria and Statistical Modeling [electronic resource]
Author(s): Sadanori Konishi
Genshiro Kitagawa
Date:2008
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Winner of the 2009 Japan Statistical Association Publication Prize. The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statisticalmodels, and numerous s uccessful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering. One of the main objectives of this book is to provide comprehensive explanations of theconcepts and derivations of the AIC and rel ated criteria, including Schwarzs Bayesian information criterion (BIC), together with a wide range of practical examples of model selection and evaluation criteria. A secondary objective isto provide a theoretical basis for the analysis and extension of i nformation criteria via a statistical functional approach. A generalized information criterion (GIC) and a bootstrap information criterion are presented, which provideunified tools for modeling and model evaluation for a diverse range of models, including various types of nonlinear models and model estimation procedures such as robust estimation, the maximum penalized likelihood method and aBayesian approach. Sadanori Konishi is Professor of Faculty of Mathematics at Kyushu University. His primary researc h interests are in multivariate analysis, statistical learning, pattern recognition and nonlinear statistical modeling.He is the editor of the Bulletin of Informatics and Cybernetics and is co-author of several Japanese books. He was awarded the Japan Sta tistical Society Prize in 2004 and is a Fellow of the American Statistical Association. GenshiroKitagawa is Director-General of the Institute of Statistical Mathematics and Professor of Statistical Science at the Graduate University for Advanced Study. Hi s primary interests are in time series analysis, non-Gaussian nonlinearfiltering and statistical modeling. He is the executive editor of the Annals of the Institute of Statistical Mathematics, co-aut
Note:Springer eBooks
Contents:Concept of statistical modeling
Statistical models
Information criterion
Statistical modeling by AIC
Generalized information criterion GIC
Statistical modeling by GIC
Theoretical development and asymptotic properties of the GIC
Bootstrap information criterion
Bayesian information criteria
Various model evaluation criteria
ISBN:9780387718873
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Data mining , Computer simulation , Bioinformatics , Mathematical statistics , Econometrics
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Call number:SPRINGER-2007-9783540735601:ONLINE Show nearby items on shelf
Title:Selected Contributions in Data Analysis and Classification [electronic resource]
Author(s): Paula Brito
Guy Cucumel
Patrice Bertrand
Francisco Carvalho
Date:2007
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This volume presents recent methodological developments in data analysis and classification. A wide range of topics is covered that includes methods for classification and clustering, dissimilarity analysis, graph analysis,consensus methods, conceptu al analysis of data, analysis of symbolic data, statistical multivariate methods, data mining and knowledge discovery in databases. Besides structural and theoretical results, the book presents a wide varietyof applications, in fields such as biology, mic ro-array analysis, cyber traffic, bank fraud detection, and text analysis. Combining new methodological advances with a wide variety of real applications, this volume is certainly ofspecial value for researchers and practitioners, providing new analytical tools that are useful in theoretical research and daily practice in classification and data analysis
Note:Springer eBooks
Contents:Analysis of Symbolic Data
Clustering Methods
Conceptual Analysis of Data
Consensus Methods
Data Analysis, Data Mining, and KDD
Dissimilarities: Structures and Indices
Multivariate Statistics
ISBN:9783540735601
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Optical pattern recognition , Mathematical statistics
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Call number:SPRINGER-2007-9783540346463:ONLINE Show nearby items on shelf
Title:Applied Partial Differential Equations [electronic resource] : A Visual Approach
Author(s): Peter A Markowich
Date:2007
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book presents selected topics in science and engineering from an applied-mathematics point of view. The described natural, socioeconomic, and engineering phenomena are modeled by partial differential equations that relatestate variables such as mass, velocity, and energy to their spatial and temporal variations. Typically, these equations are highly nonlinear in many cases they are systems, and they represent challenges even for the most modern andsophisticated mathematical and numerical-analyti c techniques. The selected topics reflect the longtime scientific interests of the author. They include flows of fluids and gases, granular-material flows, biological processes such aspattern formation on animal skins, kinetics of rarified gases, free bou ndaries, semiconductor devices, and socioeconomic processes. Each topic is briefly introduced in its scientific or engineering context, followed by a presentationof the mathematical models in the form of partial differential equations with a discussion of their basic mathematical properties. The author illustrates each chapter by a series of his own high-quality photographs, which demonstratethat partial differential equations are powerful tools for modeling a large variety of phenomena influencing our da ily lives
Note:Springer eBooks
ISBN:9783540346463
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer vision , Optical pattern recognition , Differential equations, partial , Engineering mathematics
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Call number:SPRINGER-2007-9780387374529:ONLINE Show nearby items on shelf
Title:Computational Intelligence [electronic resource] : for Engineering and Manufacturing
Author(s): Diego Andina
Duc Truong Pham
Date:2007
Publisher:Boston, MA : Springer US
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elementsof CI, centred on its key element: learning. All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial BasisFunction Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory and on to several critical applications in Engineering and Manufacturing. These are among applications where CI have excellent potential.This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors havemade critical contributions and succeeded. They have paved the road for learning paradigms tow ards the solution of many real-world problems
Note:Springer eBooks
ISBN:9780387374529
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Optical pattern recognition , Computer science , Electronics , Systems engineering
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Call number:SPRINGER-2006-9783540344162:ONLINE Show nearby items on shelf
Title:Data Science and Classification [electronic resource]
Author(s): Vladimir Batagelj
Hans-Hermann Bock
Anuka Ferligoj
Ale iberna
Date:2006
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This volume provides new methodological developments in data analysis and classification. A wide range of topics is covered that includes the measurement of similarity and dissimilarity, methods for classification and clustering,network and graph ana lyses, analysis of symbolic data, and web mining. Apart from structural and theoretical results the book shows how to apply the proposed to a variety of problems, for example in medicine, microarray analysis,social network structures, and music. The combi nation of new methodological advances with the wide range of real applications collected in this volume is of special value for researchers when choosing the appropriate among newlydeveloped analytical tools for their research problems in classification a nd data analysis
Note:Springer eBooks
Contents:Similarity and Dissimilarity
Classification and Clustering
Network and Graph Analysis
Analysis of Symbolic Data
General Data Analysis Methods
Data and Web Mining
Analysis of Music Data
Gene and Microarray Analysis
ISBN:9783540344162
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data structures (Computer science) , Information systems , Optical pattern recognition , Mathematical statistics , Economics Statistics
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Call number:SPRINGER-2006-9783540313144:ONLINE Show nearby items on shelf
Title:From Data and Information Analysis to Knowledge Engineering [electronic resource] : Proceedings of the 29th Annual Conference of the Gesellschaft fr Klassifikation e.V. University of Magdeburg, March 911, 2005/ edited by Myra Spiliopoulou, Rudolf Kr use, Christian Borgelt, Andreas Nrnberger, Wolfgang Gaul
Author(s): Myra Spiliopoulou
Rudolf Kruse
Christian Borgelt
Andreas Nrnberger
Wolfgang Gaul
Date:2006
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The volume contains revised versions of selected papers presented during the 29th Annual Conference of the Gesellschaft fr Klassifikation (GfKl), the German Classification Society, held at the Otto-von-Guericke-University ofMagdeburg, Germany, in Mar ch 2005. In addition to papers on the traditional subjects Classification, Clustering, and Data Analysis, there are many papers on a wide range of topics with a strong relation to Computer Science. Examplesare Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization. Application-oriented topics include Economics, Marketing, Banking and Finance, Medicine, Bioinformatics, Biostatistics,and Music Analysis
Note:Springer eBooks
Contents:Plenaries and Semi
plenaries
Clustering
Discriminant Analysis
Classification with Latent Variable Models
Multiway Classification and Data Analysis
Ranking, Multi
label Classification, Preferences
PLS Path Modeling, PLS Regression and Classification
Robust Methods in Multivariate Statistics
Data Mining and Explorative Multivariate Data Analysis
Text Mining
Fuzzy Data Analysis
Economics and Mining in Business Processes
Banking and Finance
Marketing
Adaptivity and Personalization
User and Data Authentication in IT Security
Bioinformatics and Biostat
ISBN:9783540313144
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Optical pattern recognition , Economics Statistics , Economics, Mathematical
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Call number:SPRINGER-2006-9780817644819:ONLINE Show nearby items on shelf
Title:Statistics and Analysis of Shapes [electronic resource]
Author(s): Hamid Krim
Anthony Yezzi
Date:2006
Publisher:Boston, MA : Birkhuser Boston
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The subject of pattern analysis and recognition pervades many aspects of our daily lives, including user authentication in banking, object retrieval from databases in the consumer sector, and the omnipresent surveillance andsecurity measures around s ensitive areas. Shape analysis, a fundamental building block in many approaches to these applications, is also used in statistics, biomedical applications (Magnetic Resonance Imaging), and many other relateddisciplines. With contributions from some of the leading experts and pioneers in the field, this self-contained, unified volume is the first comprehensive treatment of theory, methods, and algorithms, available in a single resource,without the typical quagmire of vast information scattered over a wide body of literature. Developments are discussed from a rapidly increasing number of research papers in diverse fields, including the mathematical and physicalsciences, engineering, and medicine. The initial chapters explore the statistical modeling of land marks while subsequent chapters address the probabilistic modeling of entire shapes. The latter part of the book, with the exception ofthe last two chapters, concentrates on case studies as well as implementational and practical challenges in real systems . Extensive illustrations throughout help readers overcome the sometimes terse technical details of the geometricand probabilistic formalism. Knowledge of advanced calculus and basic statistics and probability theory are the only prerequisites for the rea der. Statistics and Analysis of Shapes will be an essential learning kit for statisticalresearchers, engineers, scientists, medical researchers, and students seeking a rapid introduction to the field. It may be used as a textbook for a graduate-level spec ial topics course in statistics and signal/image analysis, or for anintensive short course on shape analysis and modeling. The state-of-the-art techniques presented will also be useful for experienced r
Note:Springer eBooks
Contents:Introduction
Medial Axis Computation and Evolution
Shape Variation of Medial Axis Representations via Principal Geodesic Analysis of Symmetric Spaces
2D Shape Modeling Using Skeletal Graphs in a Morse Theoretic Framework
Matching with Shape Contexts
Shape Recognition Based on A Contrario Methodology
Integral Invariants and Shape Matching
On the Representation of Shapes Using Implicit Functions
Computing with Point Cloud Data
Determining Intrinsic Dimension and Entropy of High
Dimensional Shape Spaces
Object
Image Metrics for Generalized Weak Perspective Projection
ISBN:9780817644819
Series:e-books
Series:SpringerLink (Online service)
Series:Modeling and Simulation in Science, Engineering and Technology
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Optical pattern recognition , Visualization , Global differential geometry , Statistics
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Call number:SPRINGER-2006-9780387352091:ONLINE Show nearby items on shelf
Title:Statistical Methods in Counterterrorism [electronic resource] : Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication
Author(s): Alyson G Wilson
Gregory D Wilson
David H Olwell
Date:2006
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:All the data was out there to warn us of this impending attack, why didn't we see it? This was a frequently asked question in the weeks and months after the terrorist attacks on the World Trade Center and the Pentagon onSeptember 11, 2001. In the wak e of the attacks, statisticians moved quickly to become part of the national response to the global war on terror. This book is an overview of the emerging research program at the intersection of nationalsecurity and statistical sciences. A wide range of talented researchers address issues in . Syndromic Surveillance---How do we detect and recognize bioterrorist events? . Modeling and Simulation---How do we better understand andexplain complex processes so that decision makers can take the best course of action? . Biometric Authentication---How do we pick the terrorist out of the crowd of faces or better match the passport to the traveler? . Game Theory---Howdo we understand the rules that terrorists are playing by? This book includes technical treatments of statistical issues that will be of use to quantitative researchers as well as more general examinations of quantitative approaches tocounterterrorism that will be accessible to decision makers with stronger policy backgrounds. Dr. Alyson G. Wilson is a statistician and the technical lead for DoD programs in the Statistical Sciences Group at Los Alamos NationalLaboratory. Dr. Gregory D. Wilson is a rhetorician and ethnographer in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. Dav id H. Olwell is chair of the Department of Systems Engineering at the Naval PostgraduateSchool in Monterey, California
Note:Springer eBooks
Contents:Game Theory
Game Theory in an Age of Terrorism: How Can Statisticians Contribute?
Combining Game Theory and Risk Analysis in Counterterrorism: A Smallpox Example
Game
Theoretic and Reliability Methods in Counterterrorism and Security
Biometric Authentication
Biometric Authentication
Towards Statistically Rigorous Biometric Authentication Using Facial Images
Recognition Problem of Biometrics: Nonparametric Dependence Measures and Aggregated Algorithms
Syndromic Surveillance
Data Analysis Research Issues and Emerging Public Health Biosurveillance Directions
Current
ISBN:9780387352091
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Optical pattern recognition , Mathematics , Operations research , Mathematical statistics , Economics, Mathematical
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Call number:SPRINGER-2006-9780387311449:ONLINE Show nearby items on shelf
Title:Case Studies in Spatial Point Process Modeling [electronic resource]
Author(s): Adrian Baddeley
Pablo Gregori
Jorge Mateu
Radu Stoica
Dietrich Stoyan
Date:2006
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology. Its further application depends greatly on good software andinstructive case studies that show the way to successful work. This book satisfies this need by a presentation of the spatstat package and many statistical examples. Researchers, spatial statisticians and scientists from biology,geosciences, materials sciences and other fields wi ll use this book as a helpful guide to the application of point process statistics. No other book presents so many well-founded point process case studies. Adrian Baddeley is Professorof Statistics at the University of Western Australia (Perth, Australia) and a Fellow of the Australian Academy of Science. His main research interests are in stochastic geometry, stereology, spatial statistics, image analysis andstatistical software. Pablo Gregori is senior lecturer of Statistics and Probability at the Depar tment of Mathematics, University Jaume I of Castellon. His research fields of interest are spatial statistics, mainly on spatial pointprocesses, and measure theory of functional analysis. Jorge Mateu is Assistant Professor of Statistics and Probability at the Department of Mathematics, University Jaume I of Castellon and a Fellow of the Spanish Statistical Societyand of Wessex Institute of Great Britain. His main research interests are in stochastic geometry and spatial statistics, mainly spatial point pr ocesses and geostatistics. Radu Stoica obtained his Ph.D. in 2001 from the University ofNice Sophia Anitpolis. He works within the biometry group at INRA Avignon. His research interests are related to the study and the simulation of point processes applie d to pattern modeling and recognition. The aimed application domainsare image processing, astronomy and environmental sciences. Dietrich Stoyan is Professor of Applied Stochastics at TU Bergakademie Fre
Note:Springer eBooks
Contents:Basic Notions and Manipulation of Spatial Point Processes
Fundamentals of Point Process Statistics
Modelling Spatial Point Patterns in R
Theoretical and Methodological Advances in Spatial Point Processes
Strong Markov Property of Poisson Processes and Slivnyak Formula
Bayesian Analysis of Markov Point Processes
Statistics for Locally Scaled Point Processes
Nonparametric Testing of Distribution Functions in Germ
grain Models
Principal Component Analysis for Spatial Point Processes Assessing the Appropriateness of the Approach in an Ecological Context
Practical App
ISBN:9780387311449
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Statistics, 0930-0325 : v185
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Distribution (Probability theory) , Mathematical statistics
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Call number:SPRINGER-2005-9783540269816:ONLINE Show nearby items on shelf
Title:Innovations in Classification, Data Science, and Information Systems [electronic resource] : Proceedings of the 27th Annual Conference of the Gesellschaft fr Klassifikation e.V., Brandenburg University of Technology,Cottbus, March 1214, 2003 / edite d by Daniel Baier, Klaus-Dieter Wernecke
Author(s): Daniel Baier
Klaus-Dieter Wernecke
Date:2005
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The volume presents innovations in data analysis and classification and gives an overview of the state of the art in these scientific fields and relevant applications. Areas that receive considerable attention in the book arediscrimination and cluste ring, data analysis and statistics, as well as applications in marketing, finance, and medicine. The reader will find material on recent technical and methodological developments and a large number ofapplications demonstrating the usefulness of the newly developed techniques
Note:Springer eBooks
Contents:Discrimination and Clustering
Probability Models and Statistical Methods
Pattern Recognition and Computational Learning
Time Series Analysis
Marketing, Retailing, and Marketing Research
Finance, Capital Markets, and Risk Management
Production, Logistics, and Controlling
Medicine and Health Services
ISBN:9783540269816
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data structures (Computer science) , Computer science , Information systems , Mathematical statistics , Management information systems
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Call number:SPRINGER-2005-9780387289816:ONLINE Show nearby items on shelf
Title:Modern Multidimensional Scaling [electronic resource] : Theory and Applications
Author(s): Ingwer Borg
Patrick J. F Groenen
Date:2005
Edition:Second Edition
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The book provides a comprehensive treatment of multidimensional scaling (MDS), a family of statistical techniques for analyzing the structure of (dis)similarity data. Such data are widespread, including, for example,intercorrelations of survey items, direct ratings on the similarity on choice objects, or trade indices for a set of countries. MDS represents the data as distances among points in a geometric space of low dimensionality. This map canhelp to see patterns in the data that are not obvious f rom the data matrices. MDS is also used as a psychological model for judgments of similarity and preference. This book may be used as an introduction to MDS for students inpsychology, sociology, and marketing. The prerequisite is an elementary background in statistics. The book is also well suited for a variety of advanced courses on MDS topics. All the mathematics required for more advanced topics isdeveloped systematically. This second edition is not only a complete overhaul of its predecessor, but also adds some 140 pages of new material. Many chapters are revised or have sections reflecting new insights and developments in MDS.There are two new chapters, one on asymmetric models and the other on unfolding. There are also numerous exercises that help t he reader to practice what he or she has learned, and to delve deeper into the models and its intricacies.These exercises make it easier to use this edition in a course. All data sets used in the book can be downloaded from the web. The appendix on comput er programs has also been updated and enlarged to reflect the state of the art. IngwerBorg is Scientific Director at the Center for Survey Methodology (ZUMA) in Mannheim, Germany, and Professor of Psychology at the University of Giessen, Germany. He has a uthored or edited 14 books and numerous articles on data analysis,survey research, theory construction, and various substantive topics of psychology. He also served as president of several professional
Note:Springer eBooks
Contents:Part I. Fundamentals of MDS: The four purposes of multidimensional scaling. Constructing MDS representations. MDS models and measures of fit. Three applications of MDS. MDS and facet theory. How to obtain proximities
Part II. MDS models and solving MDS problems. Matrix algebra for MDS. A majorization algorithm for solving MDS. Metric and non
metric MDS. Confirmatory MDS. MDS fit measures, their relations, and some algorithms. Classical scaling. Special solutions, degeneracies, and local minima III. Unfolding. Unfolding. Avoiding trivial solutions inunfolding. Special unfolding mod els
P
ISBN:9780387289816
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Optical pattern recognition , Mathematical statistics , Marketing
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Call number:SPRINGER-2004-9783662089682:ONLINE Show nearby items on shelf
Title:New Directions in Statistical Physics Econophysics, Bioinformatics, and Pattern Recognition
Author(s):
Date:2004
Size:1 online resource (22 p.)
Note:10.1007/978-3-662-08968-2
Contents:Predicting the Direction of a Time Series -- On the Variability of Timing in a Spatially Continuous System with Heterogeneous Connectivity -- First Passage Time Problem: A Fokker-Planck Approach -- First- and Last-Passage Algorithms
in Diffusion Monte Carlo -- An Updated Review of the LLS Stock Market Model: Complex Market Ecology, Power Laws in Wealth Distribution and Market Returns -- Patterns, Trends and Predictions in Stock Market Indices and Foreign Currency
Exchange Rates -- Toward an Understanding of Financial Markets Using Multi-agent Games -- Towards Understanding the Predictability of Stock Markets from the Perspective of Computational Complexity -- Patterns in Economic Phenomena --
New Algorithms and the Physics of Protein Folding -- Sequence Alignment in Bioinformatics -- Resolution of Some Paradoxes in B-Cell Binding and Activation: A Computer Study -- Proliferation and Competition in Discrete Biological
Systems -- Privacy and Data Exchanges -- Statistical Physics and the Clustering Problem -- The Challenges of Clustering High Dimensional Data -- Some Statistical Physics Approaches for Trends and Predictions in Meteorology -- An
Initial Look at Acceleration-Modulated Thermal Convection
ISBN:9783662089682
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Image processing , Biophysics , Biological physics , Statistical physics , Dynamical systems , Economic theory , Physics , Theoretical, Mathematical and Computational Physics , Image Processing and Computer Vision , Biophysics and Biological Physics , Statistical Physics, Dynamical Systems and Complexity , Economic Theory/Quantitative Economics/Mathematical Methods
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Call number:SPRINGER-2004-9783642171116:ONLINE Show nearby items on shelf
Title:Advances in Multivariate Data Analysis Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Palermo, July 5–6, 2001
Author(s):
Date:2004
Size:1 online resource (281 p.)
Note:10.1007/978-3-642-17111-6
Contents:Classification Methods with Applications -- The STP Procedure as Overfitting Avoidance Tool in Classification Trees -- A Modal Symbolic Pattern Classifier -- Proximity Measures Between Classification Trees -- Ordinal Classification
Trees Based on Impurity Measures -- Time Series Analysis and Related Methods -- Space Time Noisy Observation Smoothing -- Spectral Analysis in Frequency and Time Domain for Noisy Time Series -- A Resistant Measure of Heteroskedasticity
in Explorative Time Series Analysis -- Computer Intensive Techniques and Algorithms -- Smoothing Score Algorithm for Generalized Additive Models -- Bootstrap Variables Selection in Neural Network Regression Models -- Robust Centre
Location in Radial Basis Function Networks -- The Genetic Algorithm Estimates for the Parameters of Order p Normal Distributions -- Classification and Data Analysis in Economics -- Non-linear Dynamics in the Industrial Production Index
-- Tensorial Co-Structure Analysis for the Full Multi Modules Customer Satisfaction Evaluation -- A Proposal of Classification of Wholesale Trade Enterprises on the Base of Structural and Performance Indicators -- The Analysis of
Poverty in Italy: A Fuzzy Dynamic Approach -- Multivariate Analysis in Applied Sciences -- Combining Information from Several Experts: Selecting and Stopping Rules in Sequential Consulting -- A Spatial Clustering Hierarchical Model for
Disease Mapping -- Second-order Interaction in a Trivariate Generalized Gamma Distribution -- Mortality and Air Pollution in Philadelphia: A Dynamic Generalized Linear Modelling Approach -- The Multivariate Adaptive Sampling for
Estimating the Diversity in Biological Populations -- Adjusted Least Square Estimation for Noisy Images -- Flexible Dynamic Regression Models for Real-time Forecasting of Air Pollutant Concentration
ISBN:9783642171116
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Pattern recognition , Probabilities , Statistics , Economic theory , Mathematics , Probability Theory and Stochastic Processes , Statistics for Business/Economics/Mathematical Finance/Insurance , Economic Theory/Quantitative Economics/Mathematical Methods , Pattern Recognition , Statistics for Life Sciences, Medicine, Health Sciences
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Call number:SPRINGER-2004-9783540409861:ONLINE Show nearby items on shelf
Title:The Physics of Traffic Empirical Freeway Pattern Features, Engineering Applications, and Theory
Author(s): Boris S Kerner
Date:2004
Size:1 online resource (682 p.)
Note:10.1007/978-3-540-40986-1
Contents:1 Introduction -- I Historical Overview and Three-Phase Traffic Theory -- 2 Spatiotemporal Pattern Formation in Freeway Traffic -- 3 Overview of Freeway Traffic Theories and Models: Fundamental Diagram Approach -- 4 Basis of
Three-Phase Traffic Theory -- 5 Breakdown Phenomenon (F?S Transition) in Three-Phase Traffic Theory -- 6 Moving Jam Emergence in Three-Phase Traffic Theory -- 7 Congested Patterns at Freeway Bottlenecks in Three-Phase Traffic Theory --
8 Freeway Capacity in Three-Phase Traffic Theory -- II Empirical Spatiotemporal Congested Traffic Patterns -- 9 Empirical Congested Patterns at Isolated Bottlenecks -- 10 Empirical Breakdown Phenomenon: Phase Transition from Free Flow
to Synchronized Flow -- 11 Empirical Features of Wide Moving Jam Propagation -- 12 Empirical Features of Moving Jam Emergence -- 13 Empirical Pattern Evolution and Transformation at Isolated Bottlenecks -- 14 Empirical Complex Pattern
Formation Caused by Peculiarities of Freeway Infrastructure -- 15 Dependence of Empirical Fundamental Diagram on Congested Pattern Features -- III Microscopic Three-Phase Traffic Theory -- 16 Microscopic Traffic Flow Models for
Spatiotemporal Congested Patterns -- 17 Microscopic Theory of Phase Transitions in Freeway Traffic -- 18 Congested Patterns at Isolated Bottlenecks -- 19 Complex Congested Pattern Interaction and Transformation -- 20 Spatiotemporal
Patterns in Heterogeneous Traffic Flow -- IV Engineering Applications -- 21 ASDA and FOTO Models of Spatiotemporal Pattern Dynamics based on Local Traffic Flow Measurements -- 22 Spatiotemporal Pattern Recognition, Tracking, and
Prediction -- 23 Control of Spatiotemporal Congested Patterns -- 24 Conclusion -- A Terms and Definitions -- A.1 Traffic States, Parameters, and Variables -- A.2 Traffic Phases -- A.3 Phase Transitions -- A.4 Bottleneck Characteristics
-- A.5 Congested Patterns at Bottlenecks -- A.6 Local Perturbations -- A.7 Critical and Threshold Traffic Variables -- A.8 Some Features of Phase Transitions and Traffic State Stability -- B ASDA and FOTO Models for Practical
Applications -- B.1 ASDA Model for Several Road Detectors -- B.1.1 Extensions of ASDA for On-Ramps, Off- Ramps, and Changing of Number of Freeway Lanes Upstream of Moving Jam -- B.1.2 Extensions of ASDA for On-Ramps, Off- Ramps, and
Changing of Number of Freeway Lanes Downstream of Moving Jam -- B.1.3 FOTO Model for Several Road Detectors -- B.1.4 Extended Rules for FOTO Model -- B.2 Statistical Evaluation of Different Reduced Detector Configurations -- References
ISBN:9783540409861
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Applied mathematics , Engineering mathematics , Thermodynamics , Statistical physics , Dynamical systems , Vibration , Dynamics , Physics , Statistical Physics, Dynamical Systems and Complexity , Appl.Mathematics/Computational Methods of Engineering , Applications of Mathematics , Thermodynamics , Theoretical, Mathematical and Computational Physics , Vibration, Dynamical Systems, Control
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Call number:SPRINGER-2004-9783034879583:ONLINE Show nearby items on shelf
Title:Theory and Applications of Recent Robust Methods
Author(s):
Date:2004
Size:1 online resource (400 p.)
Note:10.1007/978-3-0348-7958-3
Contents:Bias Behavior of the Minimum Volume Ellipsoid Estimate -- A Study of Belgian Inflation, Relative Prices and Nominal Rigidities using New Robust Measures of Skewness and Tail Weight -- Robust Strategies for Quantitative Investment
Management -- An Adaptive Algorithm for Quantile Regression -- On Properties of Support Vector Machines for Pattern Recognition in Finite Samples -- Smoothed Local L-Estimation With an Application -- Fast Algorithms for Computing High
Breakdown Covariance Matrices with Missing Data -- Generalized d-fullness Technique for Breakdown Point Study of the Trimmed Likelihood Estimator with Application -- On Robustness to Outliers of Parametric L2 Estimate Criterion in the
Case of Bivariate Normal Mixtures: a Simulation Study -- Robust PCR and Robust PLSR: a Comparative Study -- Analytic Estimator Densities for Common Parameters under Misspecified Models -- Empirical Comparison of the Classification
Performance of Robust Linear and Quadratic Discriminant Analysis -- Estimates of the Tail Index Based on Nonparametric Tests -- On Mardia’s Tests of Multinormality -- Robustness in Sequential Discrimination of Markov Chains under
“Contamination” -- Robust Box-Cox Transformations for Simple Regression -- Consistency of the Least Weighted Squares Regression Estimator -- Algorithms for Robust Model Selection in Linear Regression -- Analyzing the Number of Samples
Required for an Approximate Monte-Carlo LMS Line Estimator -- Visualizing 1D Regression -- Robust Redundancy Analysis by Alternating Regression -- Robust ML-estimation of the Transmitter Location -- A Family of Scale Estimators by
Means of Trimming -- Robust Efficient Method of Moments Estimation -- Computational Geometry and Statistical Depth Measures -- Partial Mixture Estimation and Outlier Detection in Data and Regression -- Robust Fitting Using Mean Shift:
Applications in Computer Vision -- Testing the Equality of Location Parameters for Skewed Distributions Using S1 with High Breakdown Robust Scale Estimators -- Rank Scores Tests of Multivariate Independence -- The Influence of a
Stochastic Interest Rate on the n-fold Compound Option -- Robust Estimations for Multivariate Sinh-1-Normal Distribution -- A Robust Estimator of the Tail Index Based on an Exponential Regression Model -- Robust Processing of
Mechanical Vibration Measurements -- Quadratic Mixed Integer Programming Models in Minimax Robust Regression Estimators
ISBN:9783034879583
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Statistics , Statistical Theory and Methods , Statistics and Computing/Statistics Programs , Statistics for Business/Economics/Mathematical Finance/Insurance
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Call number:SPRINGER-2004-9781441990525:ONLINE Show nearby items on shelf
Title:Networks of Learning Automata Techniques for Online Stochastic Optimization
Author(s): M. A. L Thathachar
Date:2004
Size:1 online resource (268 p.)
Note:10.1007/978-1-4419-9052-5
Contents:1. Introduction -- 1.1 Machine Intelligence and Learning -- 1.2 Learning Automata -- 1.3 The Finite Action Learning Automaton (FALA) -- 1.4 Some Classical Learning Algorithms -- 1.5 The Discretized Probability FALA -- 1.6 The
Continuous Action Learning Automaton (CALA) -- 1.7 The Generalized Learning Automaton (GLA) -- 1.8 The Parameterized Learning Automaton (PLA) -- 1.9 Multiautomata Systems -- 1.10 Supplementary Remarks -- 2. Games of Learning Automata
-- 2.1 Introduction -- 2.2 A Multiple Payoff Stochastic Game of Automata -- 2.3 Analysis of the Automata Game Algorithm -- 2.4 Game with Common Payoff -- 2.5 Games of FALA -- 2.6 Common Payoff Games of CALA -- 2.7 Applications -- 2.8
Discussion -- 2.9 Supplementary Remarks -- 3. Feedforward Networks -- 3.1 Introduction -- 3.2 Networks of FALA -- 3.3 The Learning Model -- 3.4 The Learning Algorithm -- 3.5 Analysis -- 3.6 Extensions -- 3.7 Convergence to the Global
Maximum -- 3.8 Networks of GLA -- 3.9 Discussion -- 3.10 Supplementary Remarks -- 4. Learning Automata for Pattern Classification -- 4.1 Introduction -- 4.2 Pattern Recognition -- 4.3 Common Payoff Game of Automata for PR -- 4.4
Automata Network for Pattern Recognition -- 4.5 Decision Tree Classifiers -- 4.6 Discussion -- 4.7 Supplementary Remarks -- 5. Parallel Operation of Learning Automata -- 5.1 Introduction -- 5.2 Parallel Operation of FALA -- 5.3
Parallel Operation of CALA -- 5.4 Parallel Pursuit Algorithm -- 5.5 General Procedure -- 5.6 Parallel Operation of Games of FALA -- 5.7 Parallel Operation of Networks of FALA -- 5.8 Discussion -- 5.9 Supplementary Remarks -- 6. Some
Recent Applications -- 6.1 Introduction -- 6.2 Supervised Learning of Perceptual Organization in Computer Vision -- 6.3 Distributed Control of Broadcast Communication Networks -- 6.4O ther Applications -- 6.5 Discussion -- Epilogue --
Appendices -- A The ODE Approach to Analysis of Learning Algorithms -- A.I Introduction -- A.2 Derivation of the ODE Approximation -- A.2.1 Assumptions -- A.2.2 Analysis -- A.3 Approximating ODEs for Some Automata Algorithms -- A.3.2
The CALA Algorithm -- A.3.3 Automata Team Algorithms -- A.4 Relaxing the Assumptions -- B Proofs of Convergence for Pursuit Algorithm -- B.1 Proof of Theorem 1.1 -- B.2 Proof of Theorem 5.7 -- C Weak Convergence and SDE Approximations
-- C.I Introduction -- C.2 Weak Convergence -- C.3 Convergence to SDE -- C.3.1 Application to Global Algorithms -- C.4 Convergence to ODE -- References
ISBN:9781441990525
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Operations research , Decision making , Computer science , Artificial intelligence , Computational linguistics , Statistical physics , Dynamical systems , Physics , Statistical Physics, Dynamical Systems and Complexity , Artificial Intelligence (incl. Robotics) , Language Translation and Linguistics , Operation Research/Decision Theory , Computer Science, general
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Call number:SPRINGER-2004-9781441990174:ONLINE Show nearby items on shelf
Title:Mathematical Foundations of Speech and Language Processing
Author(s):
Date:2004
Size:1 online resource (289 p.)
Note:10.1007/978-1-4419-9017-4
Contents:Probability and statistics in computational linguistics, a brief review -- Three issues in modern language modeling -- Stochastic analysis of Structured Language Modeling -- Latent semantic language modeling for speech recognition --
Prosody modeling for automatic speech recognition and understanding -- Switching dynamic system models for speech articulation and acoustics -- Segmental HMMS: Modeling dynamics and underlying structure in speech -- Modelling
graph-based observation spaces for segment-based speech recognition -- Towards robust and adaptive speech recognition models -- Graphical models and automatic speech recognition -- An introduction to Markov chain Monte Carlo methods --
Semiparametric filtering in speech processing -- List of workshop participants
ISBN:9781441990174
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:The IMA Volumes in Mathematics and its Applications: 138
Keywords: Engineering , Computational linguistics , Pattern recognition , Applied mathematics , Engineering mathematics , Information theory , Engineering , Signal, Image and Speech Processing , Applications of Mathematics , Language Translation and Linguistics , Pattern Recognition , Information and Communication, Circuits
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Call number:SPRINGER-2004-9780387217796:ONLINE Show nearby items on shelf
Title:An Invitation to 3-D Vision From Images to Geometric Models
Author(s): Yi Ma
Date:2004
Size:1 online resource (528 p.)
Note:10.1007/978-0-387-21779-6
Contents:1 Introduction -- 1.1 Visual perception from 2-D images to 3-D models -- 1.2 A mathematical approach -- 1.3 A historical perspective -- I Introductory Material -- 2 Representation of a Three-Dimensional Moving Scene -- 3 Image
Formation -- 4 Image Primitives and Correspondence -- II Geometry of Two Views -- 5 Reconstruction from Two Calibrated Views -- 6 Reconstruction from Two Uncalibrated Views -- 7 Estimation of Multiple Motions from Two Views -- III
Geometry of Multiple Views -- 8 Multiple-View Geometry of Points and Lines -- 9 Extension to General Incidence Relations -- 10 Geometry and Reconstruction from Symmetry -- IV Applications -- 11 Step-by-Step Building of a 3-D Model from
Images -- 12 Visual Feedback -- V Appendices -- A Basic Facts from Linear Algebra -- A.1 Basic notions associated with a linear space -- A.1.1 Linear independence and change of basis -- A.1.2 Inner product and orthogonality -- A.1.3
Kronecker product and stack of matrices -- A.2 Linear transformations and matrix groups -- A.3 Gram-Schmidt and the QR decomposition -- A.4 Range, null space (kernel), rank and eigenvectors of a matrix -- A.5 Symmetric matrices and
skew-symmetric matrices -- A.6 Lyapunov map and Lyapunov equation -- A.7 The singular value decomposition (SVD) -- A.7.1 Algebraic derivation -- A.7.2 Geometric interpretation -- A.7.3 Some properties of the SVD -- B Least-Variance
Estimation and Filtering -- B.1 Least-variance estimators of random vectors -- B.1.1 Projections onto the range of a random vector -- B.1.2 Solution for the linear (scalar) estimator -- B.1.3 Affine least-variance estimator -- B.1.4
Properties and interpretations of the least-variance estimator -- B.2 The Kalman-Bucy filter -- B.2.1 Linear Gaussian dynamical models -- B.2.2 A little intuition -- B.2.3 Observability -- B.2.4 Derivation of the Kalman filter -- B.3
The extended Kalman filter -- C Basic Facts from Nonlinear Optimization -- C.1 Unconstrained optimization: gradient-based methods -- C.1.1 Optimality conditions -- C.1.2 Algorithms -- C.2 Constrained optimization: Lagrange multiplier
method. -- C.2.1 Optimality conditions -- C.2.2 Algorithms -- References -- Glossary of Notation
ISBN:9780387217796
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Interdisciplinary Applied Mathematics: 26
Keywords: Computer science , Computers , Computer graphics , Applied mathematics , Engineering mathematics , Geometry , Calculus of variations , Control engineering , Robotics , Mechatronics , Computer Science , Theory of Computation , Calculus of Variations and Optimal Control Optimization , Geometry , Applications of Mathematics , Computer Imaging, Vision, Pattern Recognition and Graphics , Control, Robotics, Mechatronics
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