Robustness In Statistical Pattern Recognition

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Robustness in Statistical Pattern Recognition

Author : Y. Kharin
Publisher : Springer Science & Business Media
ISBN 13 : 9780792342670
Total Pages : 326 pages
Book Rating : 4.3/5 (426 download)

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Book Synopsis Robustness in Statistical Pattern Recognition by : Y. Kharin

Download or read book Robustness in Statistical Pattern Recognition written by Y. Kharin and published by Springer Science & Business Media. This book was released on 1996-09-30 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with important problems of robust (stable) statistical pat tern recognition when hypothetical model assumptions about experimental data are violated (disturbed). Pattern recognition theory is the field of applied mathematics in which prin ciples and methods are constructed for classification and identification of objects, phenomena, processes, situations, and signals, i. e. , of objects that can be specified by a finite set of features, or properties characterizing the objects (Mathematical Encyclopedia (1984)). Two stages in development of the mathematical theory of pattern recognition may be observed. At the first stage, until the middle of the 1970s, pattern recogni tion theory was replenished mainly from adjacent mathematical disciplines: mathe matical statistics, functional analysis, discrete mathematics, and information theory. This development stage is characterized by successful solution of pattern recognition problems of different physical nature, but of the simplest form in the sense of used mathematical models. One of the main approaches to solve pattern recognition problems is the statisti cal approach, which uses stochastic models of feature variables. Under the statistical approach, the first stage of pattern recognition theory development is characterized by the assumption that the probability data model is known exactly or it is esti mated from a representative sample of large size with negligible estimation errors (Das Gupta, 1973, 1977), (Rey, 1978), (Vasiljev, 1983)).

Statistical Pattern Recognition

Author : Andrew R. Webb
Publisher : John Wiley & Sons
ISBN 13 : 0470854782
Total Pages : 516 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Statistical Pattern Recognition by : Andrew R. Webb

Download or read book Statistical Pattern Recognition written by Andrew R. Webb and published by John Wiley & Sons. This book was released on 2003-07-25 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a

Robustness in Statistical Pattern Recognition

Author : Y. Kharin
Publisher : Springer Science & Business Media
ISBN 13 : 9401586306
Total Pages : 313 pages
Book Rating : 4.4/5 (15 download)

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Book Synopsis Robustness in Statistical Pattern Recognition by : Y. Kharin

Download or read book Robustness in Statistical Pattern Recognition written by Y. Kharin and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with important problems of robust (stable) statistical pat tern recognition when hypothetical model assumptions about experimental data are violated (disturbed). Pattern recognition theory is the field of applied mathematics in which prin ciples and methods are constructed for classification and identification of objects, phenomena, processes, situations, and signals, i. e. , of objects that can be specified by a finite set of features, or properties characterizing the objects (Mathematical Encyclopedia (1984)). Two stages in development of the mathematical theory of pattern recognition may be observed. At the first stage, until the middle of the 1970s, pattern recogni tion theory was replenished mainly from adjacent mathematical disciplines: mathe matical statistics, functional analysis, discrete mathematics, and information theory. This development stage is characterized by successful solution of pattern recognition problems of different physical nature, but of the simplest form in the sense of used mathematical models. One of the main approaches to solve pattern recognition problems is the statisti cal approach, which uses stochastic models of feature variables. Under the statistical approach, the first stage of pattern recognition theory development is characterized by the assumption that the probability data model is known exactly or it is esti mated from a representative sample of large size with negligible estimation errors (Das Gupta, 1973, 1977), (Rey, 1978), (Vasiljev, 1983)).

Discriminant Analysis and Statistical Pattern Recognition

Author : Geoffrey J. McLachlan
Publisher : John Wiley & Sons
ISBN 13 : 0471725285
Total Pages : 552 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Discriminant Analysis and Statistical Pattern Recognition by : Geoffrey J. McLachlan

Download or read book Discriminant Analysis and Statistical Pattern Recognition written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2005-02-25 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." –SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.

Robustness in Statistical Forecasting

Author : Yuriy Kharin
Publisher : Springer Science & Business Media
ISBN 13 : 3319008404
Total Pages : 369 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Robustness in Statistical Forecasting by : Yuriy Kharin

Download or read book Robustness in Statistical Forecasting written by Yuriy Kharin and published by Springer Science & Business Media. This book was released on 2013-09-04 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers solutions to such topical problems as developing mathematical models and descriptions of typical distortions in applied forecasting problems; evaluating robustness for traditional forecasting procedures under distortionism and more.

Computer Vision - ACCV 2006

Author : P. J. Narayanan
Publisher : Springer Science & Business Media
ISBN 13 : 3540312447
Total Pages : 1005 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Computer Vision - ACCV 2006 by : P. J. Narayanan

Download or read book Computer Vision - ACCV 2006 written by P. J. Narayanan and published by Springer Science & Business Media. This book was released on 2006 with total page 1005 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robustness in Data Analysis

Author : Georgy L. Shevlyakov
Publisher : Walter de Gruyter
ISBN 13 : 3110936003
Total Pages : 325 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Robustness in Data Analysis by : Georgy L. Shevlyakov

Download or read book Robustness in Data Analysis written by Georgy L. Shevlyakov and published by Walter de Gruyter. This book was released on 2011-12-07 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.

Statistical Pattern Recognition

Author : Andrew R. Webb
Publisher : Newnes
ISBN 13 : 9780340741641
Total Pages : 476 pages
Book Rating : 4.7/5 (416 download)

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Book Synopsis Statistical Pattern Recognition by : Andrew R. Webb

Download or read book Statistical Pattern Recognition written by Andrew R. Webb and published by Newnes. This book was released on 1999 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an introduction to statistical pattern recognition theory and techniques. Most of the material presented in this book is concerned with discrimination and classification and has been drawn from a wide range of literature including that of engineering, statistics, computer science and the social sciences. This book is an attempt to provide a concise volume containing descriptions of many of the most useful of today's pattern processing techniques including many of the recent advances in nonparametric approaches to discrimination developed in the statistics literature and elsewhere. The techniques are illustrated with examples of real-world applications studies. Pointers are also provided to the diverse literature base where further details on applications, comparative studies and theoretical developments may be obtained"--Page [xv].

Structural, Syntactic, and Statistical Pattern Recognition

Author : Dit-Yan Yeung
Publisher : Springer Science & Business Media
ISBN 13 : 3540372369
Total Pages : 959 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Structural, Syntactic, and Statistical Pattern Recognition by : Dit-Yan Yeung

Download or read book Structural, Syntactic, and Statistical Pattern Recognition written by Dit-Yan Yeung and published by Springer Science & Business Media. This book was released on 2006-08-03 with total page 959 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the proceedings of the 11th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2006 and the 6th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2006, held in Hong Kong, August 2006 alongside the Conference on Pattern Recognition, ICPR 2006. 38 revised full papers and 61 revised poster papers are included, together with 4 invited papers covering image analysis, character recognition, bayesian networks, graph-based methods and more.

Structural, Syntactic, and Statistical Pattern Recognition

Author : Terry Caelli
Publisher : Springer
ISBN 13 : 3540706593
Total Pages : 884 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Structural, Syntactic, and Statistical Pattern Recognition by : Terry Caelli

Download or read book Structural, Syntactic, and Statistical Pattern Recognition written by Terry Caelli and published by Springer. This book was released on 2003-08-02 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains all papers presented at SSPR 2002 and SPR 2002 hosted by the University of Windsor, Windsor, Ontario, Canada, August 6-9, 2002. This was the third time these two workshops were held back-to-back. SSPR was the ninth International Workshop on Structural and Syntactic Pattern Recognition and the SPR was the fourth International Workshop on Statis- cal Techniques in Pattern Recognition. These workshops have traditionally been held in conjunction with ICPR (International Conference on Pattern Recog- tion), and are the major events for technical committees TC2 and TC1, resp- tively, of the International Association of Pattern Recognition (IAPR). The workshops were held in parallel and closely coordinated. This was an attempt to resolve the dilemma of how to deal, in the light of the progressive specialization of pattern recognition, with the need for narrow-focus workshops without further fragmenting the ?eld and introducing yet another conference that would compete for the time and resources of potential participants. A total of 116 papers were received from many countries with the submission and reviewingprocesses beingcarried out separately for each workshop. A total of 45 papers were accepted for oral presentation and 35 for posters. In addition four invited speakers presented informative talks and overviews of their research. They were: Tom Dietterich, Oregon State University, USA Sven Dickinson, the University of Toronto, Canada Edwin Hancock, University of York, UK Anil Jain, Michigan State University, USA SSPR 2002 and SPR 2002 were sponsored by the IAPR and the University of Windsor.

Robustness in Language and Speech Technology

Author : Jean-Claude Junqua
Publisher : Springer Science & Business Media
ISBN 13 : 9401597197
Total Pages : 277 pages
Book Rating : 4.4/5 (15 download)

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Book Synopsis Robustness in Language and Speech Technology by : Jean-Claude Junqua

Download or read book Robustness in Language and Speech Technology written by Jean-Claude Junqua and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book we address robustness issues at the speech recognition and natural language parsing levels, with a focus on feature extraction and noise robust recognition, adaptive systems, language modeling, parsing, and natural language understanding. This book attempts to give a clear overview of the main technologies used in language and speech processing, along with an extensive bibliography to enable topics of interest to be pursued further. It also brings together speech and language technologies often considered separately. Robustness in Language and Speech Technology serves as a valuable reference and although not intended as a formal university textbook, contains some material that can be used for a course at the graduate or undergraduate level.

Invariants for Pattern Recognition and Classification

Author : Marcos A. Rodrigues
Publisher : World Scientific
ISBN 13 : 9789812791894
Total Pages : 256 pages
Book Rating : 4.7/5 (918 download)

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Book Synopsis Invariants for Pattern Recognition and Classification by : Marcos A. Rodrigues

Download or read book Invariants for Pattern Recognition and Classification written by Marcos A. Rodrigues and published by World Scientific. This book was released on 2000 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was conceived from the realization that there was a need to update recent work on invariants in a single volume providing a useful set of references and pointers to related work. Since the publication in 1992 of J.L. Mundy and A. Zisserman's Geometric Invariance in Computer Vision, the subject has been evolving rapidly. New approaches to invariants have been proposed and novel ways of defining and applying invariants to practical problem solving are testimony to the fundamental importance of the study of invariants to machine vision. This book represents a snapshot of current research around the world. A version of this collection of papers has appeared in the International Journal of Pattern Recognition and Artificial Intelligence (December 1999). The papers in this book are extended versions of the original material published in the journal. They are organized into two categories: foundations and applications. Foundation papers present new ways of defining or analyzing invariants, and application papers present novel ways in which known invariant theory is extended and effectively applied to real-world problems in interesting and difficult contexts. Each category contains roughly half of the papers, but there is considerable overlap. All papers carry an element of novelty and generalization that will be useful to theoreticians and practitioners alike. It is hoped that this volume will be not only useful but also inspirational to researchers in image processing, pattern recognition and computer vision at large.

Robust Statistics

Author : Frank R. Hampel
Publisher : John Wiley & Sons
ISBN 13 : 1118150686
Total Pages : 502 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Robust Statistics by : Frank R. Hampel

Download or read book Robust Statistics written by Frank R. Hampel and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selectedbooks that have been made more accessible to consumers in an effortto increase global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "This is a nice book containing a wealth of information, much ofit due to the authors. . . . If an instructor designing such acourse wanted a textbook, this book would be the best choiceavailable. . . . There are many stimulating exercises, and the bookalso contains an excellent index and an extensive list ofreferences." —Technometrics "[This] book should be read carefully by anyone who isinterested in dealing with statistical models in a realisticfashion." —American Scientist Introducing concepts, theory, and applications, RobustStatistics is accessible to a broad audience, avoidingallusions to high-powered mathematics while emphasizing ideas,heuristics, and background. The text covers the approach based onthe influence function (the effect of an outlier on an estimater,for example) and related notions such as the breakdown point. Italso treats the change-of-variance function, fundamental conceptsand results in the framework of estimation of a single parameter,and applications to estimation of covariance matrices andregression parameters.

Robustness and Complex Data Structures

Author : Claudia Becker
Publisher : Springer Science & Business Media
ISBN 13 : 3642354947
Total Pages : 377 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Robustness and Complex Data Structures by : Claudia Becker

Download or read book Robustness and Complex Data Structures written by Claudia Becker and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Festschrift in honour of Ursula Gather’s 60th birthday deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading experts provide a textbook-style overview of the topic, supplemented by current research results and questions. The statistical theory and methods in this volume aim at the analysis of data which deviate from classical stringent model assumptions, which contain outlying values and/or have a complex structure. Written for researchers as well as master and PhD students with a good knowledge of statistics.

Robust Correlation

Author : Georgy L. Shevlyakov
Publisher : John Wiley & Sons
ISBN 13 : 1119264537
Total Pages : 352 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Robust Correlation by : Georgy L. Shevlyakov

Download or read book Robust Correlation written by Georgy L. Shevlyakov and published by John Wiley & Sons. This book was released on 2016-08-02 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.

Pattern Recognition and Machine Learning

Author : Christopher M. Bishop
Publisher : Springer
ISBN 13 : 9781493938438
Total Pages : 0 pages
Book Rating : 4.9/5 (384 download)

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Book Synopsis Pattern Recognition and Machine Learning by : Christopher M. Bishop

Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Robust Methods in Biostatistics

Author : Stephane Heritier
Publisher : John Wiley & Sons
ISBN 13 : 9780470740545
Total Pages : 292 pages
Book Rating : 4.7/5 (45 download)

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Book Synopsis Robust Methods in Biostatistics by : Stephane Heritier

Download or read book Robust Methods in Biostatistics written by Stephane Heritier and published by John Wiley & Sons. This book was released on 2009-05-11 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated models as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regression Generalized linear models Linear mixed models Marginal longitudinal data models Cox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.