Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
(Part of the Complex Adaptive Systems Series)
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Book Overview
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.
Format:Paperback
Language:English
ISBN:0262527901
ISBN13:9780262527903
Release Date:June 2001
Publisher:MIT Press
Length:576 Pages
Weight:2.00 lbs.
Dimensions:1.3" x 7.0" x 8.9"
Age Range:18 years and up
Grade Range:Postsecondary and higher
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