ISBN: 9789048147601

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)). Books > Computers > Artificial Intelligence List_Books

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2010, ISBN: 9789048147601

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)). Buch (fremdspr.) Y. Kharin Taschenbuch, Springer Netherland, 15.12.2010, Springer Netherland, 2010

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2010, ISBN: 9048147603

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Softcover reprint of hardcover 1st ed. 1996 Kartoniert / Broschiert Wahrscheinlichkeitsrechnung und Statistik, Angewandte Mathematik, Künstliche Intelligenz, Digitale Signalverarbeitung (DSP), classification; clusteranalysis; Cognition; Control; cybernetics; mathematics; modeling; patternrecognition, mit Schutzumschlag 11, [PU:Springer Netherlands; Springer Netherland]

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2010, ISBN: 9048147603

Hardcover

Softcover reprint of hardcover 1st ed. 1996 Kartoniert / Broschiert Angewandte Mathematik, Elektronik, Künstliche Intelligenz, Digitale Signalverarbeitung (DSP), classification; clusteranalysis; Cognition; Control; cybernetics; mathematics; modeling; patternrecognition, mit Schutzumschlag 11, [PU:Springer Netherlands; Springer Netherland]

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ISBN: 9048147603

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ISBN: 9789048147601

This book is concerned with important problems of robust (stable) statistical pat tern recognition when hypothetical model assumptions about experimental data are violated &… More...

2010, ISBN: 9789048147601

This book is concerned with important problems of robust (stable) statistical pat tern recognition when hypothetical model assumptions about experimental data are violated (disturbed). Pa… More...

2010

## ISBN: 9048147603

Hardcover

Softcover reprint of hardcover 1st ed. 1996 Kartoniert / Broschiert Wahrscheinlichkeitsrechnung und Statistik, Angewandte Mathematik, Künstliche Intelligenz, Digitale Signalverarbeitung… More...

2010, ISBN: 9048147603

Hardcover

Softcover reprint of hardcover 1st ed. 1996 Kartoniert / Broschiert Angewandte Mathematik, Elektronik, Künstliche Intelligenz, Digitale Signalverarbeitung (DSP), classification; cluster… More...

ISBN: 9048147603

Hardcover

Robustness in Statistical Pattern Recognition ab 138.99 € als Taschenbuch: Softcover reprint of hardcover 1st ed. 1996. Aus dem Bereich: Bücher, Taschenbücher, Naturwissenschaft, Springer… More...

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** Details of the book - Robustness in Statistical Pattern Recognition**

EAN (ISBN-13): 9789048147601

ISBN (ISBN-10): 9048147603

Hardcover

Paperback

Publishing year: 2010

Publisher: Springer Netherlands Core >1

320 Pages

Weight: 0,485 kg

Language: eng/Englisch

Book in our database since 2012-10-30T22:48:27-04:00 (New York)

Detail page last modified on 2022-02-22T06:31:21-05:00 (New York)

ISBN/EAN: 9789048147601

ISBN - alternate spelling:

90-481-4760-3, 978-90-481-4760-1

### Information from Publisher

Author: Y. Kharin

Title: Mathematics and Its Applications; Robustness in Statistical Pattern Recognition

Publisher: Springer; Springer Netherland

302 Pages

Publishing year: 2010-12-15

Dordrecht; NL

Printed / Made in

Weight: 0,842 kg

Language: English

139,09 € (DE)

142,99 € (AT)

153,50 CHF (CH)

POD

XIV, 302 p.

BC; Previously published in hardcover; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; classification; cluster analysis; cognition; control; cybernetics; mathematics; modeling; pattern recognition; B; Statistics, general; Applications of Mathematics; Artificial Intelligence; Signal, Image and Speech Processing; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Statistics; Applications of Mathematics; Artificial Intelligence; Signal, Speech and Image Processing; Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Mathematics and Statistics; Angewandte Mathematik; Künstliche Intelligenz; Elektronik; Digitale Signalverarbeitung (DSP); Wahrscheinlichkeitsrechnung und Statistik; BB

Preface. 1. Probability Models of Data and Optimal Decision Rules. 2. Violations of Model Assumptions and Basic Notions in Decision Rule Robustness. 3. Robustness of Parametric Decision Rules and Small-Sample Effects. 4. Robustness of Nonparametric Decision Rules and Small-Sample Effects. 5. Decision Rule Robustness under Distortions of Observations to be Classified. 6. Decision Rule Robustness under Distortions of Training Samples. 7. Cluster Analysis under Distorted Model Assumptions. Bibliography. Index. Main Notations and Abbreviations.### More/other books that might be very similar to this book

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