Neural Computing - An Introduction [Paperback]

R Beale (Author), T Jackson (Author)

Book Description

ISBN-10: 0852742622 | ISBN-13: 978-0852742624 | Publication Date: January 1, 1990

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

• Paperback: 240 pages
• Publisher: Institute of Physics Publishing (January 1, 1990)
• Language: English
• ISBN-10: 0852742622
• ISBN-13: 978-0852742624
• Product Dimensions: 8.9 x 6.1 x 0.6 inches
• Shipping Weight: 14.1 ounces (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #1,250,269 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

15 of 16 people found the following review helpful:

5.0 out of 5 stars An excellent introduction to Neural Networks, June 10, 1997

By A Customer

This review is from: Neural Computing - An Introduction (Paperback)

This book is a great introduction to the subject of Neural Networks for someone with no background in the field. The book clearly presents a wide range of techniques for neural computing with sections dedicated to the background of the technique, algorithms for implementing the technique, the mathematics behind the algorithms, and examples where such networks have been used. All of the challenging mathematics are set aside in clearly marked sections which can be skipped by those not interested in the details. The language of the book is intentionally accessible, and the authors carefully indicate where neural networks are like and unlike real brain activity.

Each chapter has a bibliography indicating further references. Many are the actualy primary sources written by those who researched the field or technique discussed. For one instance, when the authors had changed terminology from a source for clarity, they even explained the words used by the original author to fascilitate studying the original sources.

For someone who has heard of neural networks but lacks a full understanding of what they do and how they work, this book is an excellent choice. After every chapter I was filled with a longing to go write a neural network to play with.