Pattern Classification: A Unified View of Statistical and Neural Approaches

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9780471135340: Pattern Classification: A Unified View of Statistical and Neural Approaches
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PATTERN CLASSIFICATION

a unified view of statistical and neural approaches

The product of years of research and practical experience inpattern classification, this book offers a theory-based engineeringperspective on neural networks and statistical patternclassification. Pattern Classification sheds new light on therelationship between seemingly unrelated approaches to patternrecognition, including statistical methods, polynomial regression,multilayer perceptron, and radial basis functions. Important topicssuch as feature selection, reject criteria, classifier performancemeasurement, and classifier combinations are fully covered, as wellas material on techniques that, until now, would have required anextensive literature search to locate. A full program ofillustrations, graphs, and examples helps make the operations andgeneral properties of different classification approachesintuitively understandable.

Offering a lucid presentation of complex applications and theiralgorithms, Pattern Classification is an invaluable resource forresearchers, engineers, and graduate students in this rapidlydeveloping field.

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From the Publisher:

Based on many years of practical experience predominately in the area of character recognition and document analysis, the author details a number of competing approaches to building up essential estimating functions--statistical modeling, least mean squares techniques and radial basis functions. Traditional statistics-based pattern classification techniques as well as connectionist and neural methods are coherently treated and shown to be inextricably interfused. Uses an extremely simplified two-dimensional example task throughout the text to illustrate diverse approaches in a unified manner.

About the Author:

JÜRGEN SCHÜRMANN is head of the Pattern UnderstandingGroup at the Daimler-Benz Research Center in Ulm, Germany, andteaches at the Technical University of Darmstadt.

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Book Description John Wiley and Sons Ltd, United States, 1996. Hardback. Condition: New. 1. Auflage. Language: English. Brand new Book. 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. Seller Inventory # AAH9780471135340

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Book Description John Wiley and Sons Ltd, United States, 1996. Hardback. Condition: New. 1. Auflage. Language: English. Brand new Book. 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. Seller Inventory # AAH9780471135340

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