Neural Networks in a Softcomputing Framework

Du, Ke-Lin; Swamy, M.N.S.

Conventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system. Neural networks are a model-free, adaptive, parallel-processing solution. This textbook provides a powerful and universal paradigm for information processing; it reviews the most popular neural-network methods and their associated techniques.

Each chapter has a systematic survey of each neural-network model. Computational intelligence topics like fuzzy logic and genetic algorithms (tools for neural-network learning) are introduced. Array signal processing problems are used to show the applications of each model.

This is an ideal textbook for graduate students and researchers; as well as introducing the basics, the exhaustive list of references included will aid their future research. It is also a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and A.I.

Details

Published by: Springer

Publication Date: 2010-10-13

Format: Paperback

ISBN-13: 9781849965743

DOI: 10.1007/1-84628-303-5

Dimensions: 235cm x155cm

Pages: 566