PATTERN RECOGNITION: STATISTICAL, STRUCTURAL AND NEURAL APPROACHES
PATTERN RECOGNITION: STATISTICAL, STRUCTURAL AND NEURAL APPROACHES

Author: Schalkoff

Publisher: John Wiley & Sons

Published: 2007-09

Total Pages: 388

ISBN-13: 9788126513703

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About The Book: This book explores the heart of pattern recognition concepts, methods and applications using statistical, syntactic and neural approaches. Divided into four sections, it clearly demonstrates the similarities and differences among the three approaches. The second part deals with the statistical pattern recognition approach, starting with a simple example and finishing with unsupervised learning through clustering. Section three discusses the syntactic approach and explores such topics as the capabilities of string grammars and parsing; higher dimensional representations and graphical approaches. Part four presents an excellent overview of the emerging neural approach including an examination of pattern associations and feedforward nets. Along with examples, each chapter provides the reader with pertinent literature for a more in-depth study of specific topics.

Pattern Recognition
Pattern Recognition

Author: Robert J. Schalkoff

Publisher: John Wiley & Sons

Published: 1992

Total Pages: 392

ISBN-13:

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Explores the heart of pattern recognition concepts, methods and applications using statistical, syntactic and neural approaches. Divided into four sections, it clearly demonstrates the similarities and differences among the three approaches. The second part deals with the statistical pattern recognition approach, starting with a simple example and finishing with unsupervised learning through clustering. Section three discusses the syntactic approach and explores such topics as the capabilities of string grammars and parsing; higher dimensional representations and graphical approaches. Part four presents an excellent overview of the emerging neural approach including an examination of pattern associations and feedforward nets. Along with examples, each chapter provides the reader with pertinent literature for a more in-depth study of specific topics.

Pattern Recognition
Pattern Recognition

Author: Robert J. Schalkoff

Publisher:

Published: 1992

Total Pages: 364

ISBN-13: 9780471552383

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The heart of pattern recognition concepts, methods and applications are explored in this textbook, using statistical, syntactic and neural approaches. The book clearly demonstrates the similarities and differences among the three approaches and each chapter provides the reader with examples and pertinent literature for a more in-depth study of specific topics.

Statistical Pattern Recognition
Statistical Pattern Recognition

Author: Andrew R. Webb

Publisher: John Wiley & Sons

Published: 2003-07-25

Total Pages: 516

ISBN-13: 0470854782

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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

Introduction to Pattern Recognition
Introduction to Pattern Recognition

Author: Menahem Friedman

Publisher: World Scientific

Published: 1999

Total Pages: 350

ISBN-13: 9789810233129

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This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.

Syntactic and Structural Pattern Recognition
Syntactic and Structural Pattern Recognition

Author: Horst Bunke

Publisher: World Scientific

Published: 1990

Total Pages: 568

ISBN-13: 9789971505660

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This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.

Handbook Of Pattern Recognition And Computer Vision (2nd Edition)
Handbook Of Pattern Recognition And Computer Vision (2nd Edition)

Author: Chi Hau Chen

Publisher: World Scientific

Published: 1999-03-12

Total Pages: 1045

ISBN-13: 9814497649

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The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.

Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition

Author: Christopher M. Bishop

Publisher: Oxford University Press

Published: 1995-11-23

Total Pages: 501

ISBN-13: 0198538642

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Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.

Introduction To Pattern Recognition: Statistical, Structural, Neural And Fuzzy Logic Approaches
Introduction To Pattern Recognition: Statistical, Structural, Neural And Fuzzy Logic Approaches

Author: Menahem Friedman

Publisher: World Scientific Publishing Company

Published: 1999-03-01

Total Pages: 343

ISBN-13: 9813105186

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This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.