Neural Computing - An Introduction / Edition 1

by R Beale, T Jackson

Overview

Neural computing is one of the most interesting and rapidly growing areas of research, attracting researchers from a wide variety of scientific disciplines. Starting from the basics, Neural Computing covers all the major approaches, putting each in perspective in terms of their capabilities, advantages, and disadvantages. The book also highlights the applications of each approach and explores the relationships among models developed and between the brain and its function.

A comprehensive and comprehensible introduction to the subject, this book is ideal for undergraduates in computer science, physicists, communications engineers, workers involved in artificial intelligence, biologists, psychologists, and physiologists.

Product Details

ISBN-13:	9781138413092
Publisher:	Taylor & Francis
Publication date:	07/27/2017
Pages:	256
Product dimensions:	6.12(w) x 9.19(h) x (d)

Table of Contents

Introduction. Pattern recognition. The basic neuron. The multi-layer perceptron. Kohonen self-organizing networks. Hopfield networks. Adaptive resonance theory. Associative memory. Into the looking glass. Index.

Editorial Reviews

"Neural Computing is easy on the eye with a good layout and use of graphical icons to draw attention to mathematical proofs, algorithms (in clear format, which would lend itself to computer implementation), and summary sections."
-Denise Gorse, Times Higher Education Supplement

"… most accessible. … I was most impressed with the quality of this book. … hard pressed to beat …"
-David Williams, The Australian Computer Journal

"It is clear that any introductory book must explain what the leaders of the current revival have done. This is well done by Beale and Jackson."
-Igor Aleksander, Imperial College of Science, Technology and Medicine, London, UK

From the Publisher