Neural Network Principles

Neural Network Principles

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This text presents basic ideas of neural networks (theory, design and principles) in mathematical form - using models of biological systems as springboards to a broad range of applications. The book outlines the structure of the human brain, explains the physics of neurons and derives the standard neuron state equations - then presents the consequences of these mathematical models. It also: derives a set of simple networks that can filter, recall, switch, amplify and recognise input signals; discusses properties of general interconnected neuron groups; applies the theory to synthesize artificial neural networks for special tasks; outlines the design of machine vision systems; explores motor control of the human brain and presents two examples of artificial hand-eye systems; shows how to solve large systems of interconnected neurons; considers control and modulationin the human brain/mind - with insights for a new understanding of many mental illnesses; and discusses some philosophical issues - especially consciousness from a neural network view.
This text is intended for use on undergraduate and graduate level courses in neural networks in departments of electrical engineering, computer science and psychology.
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Product details

  • Paperback | 464 pages
  • 180 x 235mm | 300g
  • Pearson Education Limited
  • Prentice-Hall
  • Harlow, United Kingdom
  • bibliography, glossary, index
  • 0131121944
  • 9780131121942

Table of contents

Neuron physics and state equations; simple networks; complex networks; vision systems; hand-eye systems; advanced design methods; brain control and modulation systems; philosophical implications.
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