Pattern Classification

Author : Richard O. Duda,Peter E. Hart,David G. Stork
Publisher : John Wiley & Sons
Page : 680 pages
File Size : 53,9 Mb
Release : 2012-11-09
Category : Technology & Engineering
ISBN : 9781118586006

Get Book

Pattern Classification by Richard O. Duda,Peter E. Hart,David G. Stork Pdf

The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

Author : Geoff Dougherty
Publisher : Springer Science & Business Media
Page : 203 pages
File Size : 49,5 Mb
Release : 2012-10-28
Category : Computers
ISBN : 9781461453239

Get Book

Pattern Recognition and Classification by Geoff Dougherty Pdf

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.

Author : Jgen Schmann
Publisher : Wiley-Interscience
Page : 424 pages
File Size : 53,9 Mb
Release : 1996-03-15
Category : Business & Economics
ISBN : UOM:39015037276188

Get Book

Pattern Classification by Jgen Schmann Pdf

PATTERN CLASSIFICATION a unified view of statistical and neural approaches The product of years of research and practical experience in pattern classification, this book offers a theory-based engineering perspective on neural networks and statistical pattern classification. Pattern Classification sheds new light on the relationship between seemingly unrelated approaches to pattern recognition, including statistical methods, polynomial regression, multilayer perceptron, and radial basis functions. Important topics such as feature selection, reject criteria, classifier performance measurement, and classifier combinations are fully covered, as well as material on techniques that, until now, would have required an extensive literature search to locate. A full program of illustrations, graphs, and examples helps make the operations and general properties of different classification approaches intuitively understandable. Offering a lucid presentation of complex applications and their algorithms, Pattern Classification is an invaluable resource for researchers, engineers, and graduate students in this rapidly developing field.

Author : Shigeo Abe
Publisher : Springer Science & Business Media
Page : 332 pages
File Size : 51,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781447102854

Get Book

Pattern Classification by Shigeo Abe Pdf

This book provides a unified approach for developing a fuzzy classifier and explains the advantages and disadvantages of different classifiers through extensive performance evaluation of real data sets. It thus offers new learning paradigms for analyzing neural networks and fuzzy systems, while training fuzzy classifiers. Function approximation is also treated and function approximators are compared.

Author : Sergios Theodoridis,Konstantinos Koutroumbas
Publisher : Elsevier
Page : 689 pages
File Size : 41,8 Mb
Release : 2003-05-15
Category : Technology & Engineering
ISBN : 008051362X

Get Book

Pattern Recognition by Sergios Theodoridis,Konstantinos Koutroumbas Pdf

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms. *Approaches pattern recognition from the designer's point of view *New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere *Supplemented by computer examples selected from applications of interest

Author : Brian D. Ripley
Publisher : Cambridge University Press
Page : 420 pages
File Size : 43,7 Mb
Release : 2007
Category : Computers
ISBN : 0521717701

Get Book

Pattern Recognition and Neural Networks by Brian D. Ripley Pdf

This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.

Author : Luc Devroye,Laszlo Györfi,Gabor Lugosi
Publisher : Springer Science & Business Media
Page : 631 pages
File Size : 40,9 Mb
Release : 2013-11-27
Category : Mathematics
ISBN : 9781461207115

Get Book

A Probabilistic Theory of Pattern Recognition by Luc Devroye,Laszlo Györfi,Gabor Lugosi Pdf

A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.

Author : Albert Nigrin
Publisher : MIT Press
Page : 450 pages
File Size : 54,5 Mb
Release : 1993
Category : Computers
ISBN : 0262140543

Get Book

Neural Networks for Pattern Recognition by Albert Nigrin Pdf

In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural networks by Stephen Grossberg and his colleagues to a new level. In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Following a tutorial of existing neural networks for pattern classification, Nigrin expands on these networks to present fundamentally new architectures that perform realtime pattern classification of embedded and synonymous patterns and that will aid in tasks such as vision, speech recognition, sensor fusion, and constraint satisfaction. Nigrin presents the new architectures in two stages. First he presents a network called Sonnet 1 that already achieves important properties such as the ability to learn and segment continuously varied input patterns in real time, to process patterns in a context sensitive fashion, and to learn new patterns without degrading existing categories. He then removes simplifications inherent in Sonnet 1 and introduces radically new architectures. These architectures have the power to classify patterns that may have similar meanings but that have different external appearances (synonyms). They also have been designed to represent patterns in a distributed fashion, both in short-term and long-term memory.

Author : Keinosuke Fukunaga
Publisher : Elsevier
Page : 592 pages
File Size : 54,6 Mb
Release : 2013-10-22
Category : Computers
ISBN : 9780080478654

Get Book

Introduction to Statistical Pattern Recognition by Keinosuke Fukunaga Pdf

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.

Author : Christopher M. Bishop
Publisher : Springer
Page : 0 pages
File Size : 44,7 Mb
Release : 2016-08-23
Category : Computers
ISBN : 1493938436

Get Book

Pattern Recognition and Machine Learning by Christopher M. Bishop Pdf

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.

Author : Mitra Basu,Tin Kam Ho
Publisher : Springer Science & Business Media
Page : 309 pages
File Size : 52,6 Mb
Release : 2006-12-22
Category : Computers
ISBN : 9781846281723

Get Book

Data Complexity in Pattern Recognition by Mitra Basu,Tin Kam Ho Pdf

Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 41,8 Mb
Release : 2024-06-23
Category : Electronic
ISBN : 9789814468312

Get Book

Pattern Classification Using Ensemble Methods by Anonim Pdf

Author : Christopher M. Bishop
Publisher : Oxford University Press
Page : 501 pages
File Size : 55,5 Mb
Release : 1995-11-23
Category : Computers
ISBN : 9780198538646

Get Book

Neural Networks for Pattern Recognition by Christopher M. Bishop Pdf

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.

Author : Shai Shalev-Shwartz,Shai Ben-David
Publisher : Cambridge University Press
Page : 415 pages
File Size : 45,7 Mb
Release : 2014-05-19
Category : Computers
ISBN : 9781107057135

Get Book

Understanding Machine Learning by Shai Shalev-Shwartz,Shai Ben-David Pdf

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Author : Witold Pedrycz,Shyi-Ming Chen
Publisher : Springer
Page : 428 pages
File Size : 53,5 Mb
Release : 2018-04-30
Category : Technology & Engineering
ISBN : 9783319896298

Get Book

Computational Intelligence for Pattern Recognition by Witold Pedrycz,Shyi-Ming Chen Pdf

The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.