Research Catalog

Title

Neural computing : an introduction / R. Beale and T. Jackson.

Author

Beale, R. (Russell)

Publication

Bristol : Hilger, ©1990.

Items in the Library & Off-site

Details

Additional Authors

Jackson, T. (Tom)

Description

xv, 240 p. : ill.; 24 cm.

Summary

An explanation of the basic concepts of neural computation, this book is about the whole field of neural networks and covers the major approaches and their results. It aims to develop concepts and ideas from their simple basics through their formulation into power computational systems.

Subject

• Artificial intelligence
• Artificial Intelligence
• artificial intelligence
• Neurocomputer
• Neuronales Netz
• Neurale netwerken
• Kunstmatige intelligentie

Bibliography (note)

• Includes bibliographical references and index.

Contents

1. Introduction; 1.1 Humans and computers; 1.2 The structure of the brain; 1.3 Learning in machines; 1.4 The differences; 2 Pattern recognition; 2.1 Introduction; 2.2 Pattern recognition in perspective; 2.3 Pattern recognition -- a definition; 2.4 Feature vectors and feature space; 2.5 Discriminant functions; 2.6 Classification techniques; 2.7 Linear classifiers; 2.8 Statistical techniques; 3 The basic neuron; 3.1 Introduction; 3.2 Modelling the single neuron; 3.3 Learning in simple neurons; 3.4 The perceptron: a vectorial perspective; 3.5 The perceptron learning rule: proof; 3.6 Limitations of perceptrons; 3.7 The end of the line?; 4 The multilayer perceptron; 4.1 Introduction; 4.2 Altering the perceptron model; 4.3 The new model; 4.4 The new learning rule; 4.5 The multilayer perceptron algorithm; 4.6 The XOR problem revisited; 4.7 Visualising network behaviour; 4.8 Multilayer perceptrons as classifiers; 4.9 Generalisation; 4.10 Fault tolerance; 4.11 Learning difficulties; 4.12 Radial basis functions; 4.13 Applications; 5 Kohonen self-organising networks; 5.1 Introduction; 5.2 The Kohonen algorithm; 5.3 Weight training; 5.4 Neighbourhoods; 5.5 Reducing the neighbourhood; 5.6 Learning vector quantisation (LVQ); 5.7 The phonetic typewriter; 6 Hopfield networks; 6.1 Introduction; 6.2 The Hopfield model; 6.3 The energy landscape; 6.4 The Boltzmann machine; 6.5 Constraint satisfaction; 7 Adaptive resonance memory; 7.1 Introduction; 7.2 Adaptive resonance theory -- ART; 7.3 Architecture and operation; 7.4 ART algorithm; 7.5 Training the ART network; 7.6 Classification; 7.7 Conclusion; 7.8 Summary of ART; 8 Associative memory; 8.1 Standard computer memory; 8.2 Implementing associative memory; 8.3 Implementing RAMs; 8.4 RAMs and n-tupling; 8.5 Willshaw's associative net; 8.6 The ADAM system; 8.7 Kanerva's sparse distributed memory; 8.8 Bidirectiona; associative memories; 9 Into the looking glass; 9.1 Overview; 9.2 Hardware and software implementations; 9.3 Optical computing; 9.4 Optical computing and neural networks.

ISBN

• 0852742622
• 9780852742624

LCCN

9780852742624

OCLC

• ocm21974403
• 21974403
• SCSB-9168530

Owning Institutions

Princeton University Library