Learning and soft computing : support vector machines, neural networks, and fuzzy logic models

Vojislav Kecman

This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.

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この本の情報

書名 Learning and soft computing : support vector machines, neural networks, and fuzzy logic models
著作者等 Kecman, V.
Kecman Vojislav
シリーズ名 Complex adaptive systems
Bradford book
出版元 MIT Press
刊行年月 c2001
ページ数 xxxii, 541 p.
大きさ 24 cm
ISBN 0262112558
NCID BA52481084
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言語 英語
出版国 アメリカ合衆国
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