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Description - Learning and Soft Computing by Vojislav Kecman

This textbook provides an 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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Book Details

ISBN: 9780262112550
ISBN-10: 0262112558
Format: Hardback
(229mm x 178mm x 31mm)
Pages: 576
Imprint: Bradford Books
Publisher: MIT Press Ltd
Publish Date: 8-Jun-2001
Country of Publication: United States

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Author Biography - Vojislav Kecman

Vojislav Kecman is in the Department of Mechanical Engineering, University of Auckland.