Título: Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Autor: V. Kecman, Vojislav Kecman
Sinopse: 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.
Contexto da obra
Quando a classificação é mais ampla, o contexto do livro costuma depender ainda mais de autoria, tema e edição. “Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models”, de V. Kecman, Vojislav Kecman, publicado pela editora Bradford Book, em 2001 e com 576 páginas, integra a categoria Livros Variados. Por isso, autoria, edição e tema acabam tendo ainda mais peso na forma de apresentar o livro.
Editora: Bradford Book
Páginas: 576
Ano: 2001
Edição: 1
Linguagem: pt_BR
ISBN: 9780262112550
ISBN13: 9780262112550
