Guide to Neural Computing Applications

1st Edition

Authors: Lionel Tarassenko
Print ISBN: 9780340705896
eBook ISBN: 9780080512600
Imprint: Butterworth-Heinemann
Published Date: 30th January 1998
Page Count: 160
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Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of data into orderly and informative patterns but they cannot solve every problem and consequently their application must be chosen carefully and appropriately.

This book outlines how best to make use of neural networks. It enables newcomers to the technology to construct robust and meaningful non-linear models and classifiers and benefits the more experienced practitioner who, through over familiarity, might otherwise be inclined to jump to unwarranted conclusions. The book is an invaluable resource not only for those in industry who are interested in neural computing solutions, but also for final year undergraduates or graduate students who are working on neural computing projects. It provides advice which will help make the best use of the growing number of commercial and public domain neural network software products, freeing the specialist from dependence upon external consultants.


Professional engineers, industrial managers, postgraduates and researchers in computer science/electronic engineering.

Table of Contents

Mathematical background for neural computing Managing a neural computing project Identifying applications and assessing their feasibility Neural computing hardware and software Collecting and preparing data Designing, training and testing of the prototype Case studies Error propagation algorithm for weight updated in a MLP Use of Bayes theorem to compensate for different prior probabilities.


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© Butterworth-Heinemann 1998
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About the Author

Lionel Tarassenko

Affiliations and Expertise

Professor of Electrical and Electronic Engineering, Oxford University, UK


An excellent tutorial and practical users guide - far more accessible than the competition.,Professor Alan F. Murray, University of Edinburgh, UK. ... deserves a place on the neural network practitioners bookshelf ...,Proceedings of the Institution of Electrical Engineers,