Neural Computing - An Introduction - Brossura

Beale, R.

Brossura

ISBN 10: 0852742622 ISBN 13: 9780852742624

Casa editrice: Routledge, 1990

Riassunto

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.

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Contenuti

INTRODUCTION
Humans and computers
The structure of the brain
Learning in machines
The differences
Summary

PATTERN RECOGNITION
Introduction
Pattern recognition in perspective
Pattern recognition-a definition
Feature vectors and feature space
Discriminant functions
Classification techniques
Linear classifiers
Statistical techniques
Pattern recognition-a summary

THE BASIC NEURON
Introduction
Modeling the single neuron
Learning in simple neurons
The perceptron: a vectorial perspective
The perceptron learning rule: proof
Limitations of perceptrons
The end of the line?
Summary

THE MULTILAYER PERCEPTRON
Introduction
Altering the perceptron model
The new model
The new learning rule
The multilayer perceptron algorithm
The XOR problem revisited
Visualizing network behavior
Multilayer perceptrons as classifiers
Generalization
Fault tolerance
Learning difficulties
Radial basis functions
Applications
Summary

KOHONEN SELF-ORGANIZING NETWORKS
Introduction
The Kohonen algorithm
Weight training
Neighborhoods
Reducing the neighborhood
Learning vector quantization (LVQ)
The phonetic typewriter
Summary

HOPFIELD NETWORKS
Introduction
The Hopfield model
The energy landscape
The Boltzmann machine
Constraint satisfaction
Summary

ADAPTIVE RESONANCE THEORY
Introduction
Adaptive resonance theory (ART)
Architecture and operation
ART algorithm
Training the ART network
Classification
Conclusion
Summary of ART

ASSOCIATIVE MEMORY
Standard computer memory
Implementing associative memory
Implementation in RAMs
RAMs and N-tupling
Willshaw's associative net
The ADAM system
Kanerva's sparse distributed memory
Bidirectional associative memories
Conclusion
Summary

INTO THE LOOKING GLASS
Overview
Hardware and software implementations
Optical computing
Optical computing and neural networks

INDEX

Product Description

Book by Beale R Jackson T

Dettagli dell?edizione

• Editore: Routledge
• Data di pubblicazione: 1990
• ISBN 10: 0852742622
• ISBN 13: 9780852742624
• Rilegatura: Copertina flessibile
• Lingua: Inglese
• Numero edizione: 1
• Numero di pagine: 256