The handbook of brain theory and neural networks

Bibliographic Information

The handbook of brain theory and neural networks

edited by Michael A. Arbib ; editorial advisory board, George Adelman ... [et al.] ; editorial assistant, Prudence H. Arbib

MIT Press, 1998, c1995

  • : pbk

Available at  / 54 libraries

Search this Book/Journal

Note

"A Bradford book."

Errata slip inserted

Originally published 1995

Includes bibliographical references and index

Description and Table of Contents

Description

This text charts the progress made in recent years in many specific areas related to the following two questions: how does the brain work?; and how can we build intelligent machines? The handbook covers the entire range of topics involved in brain theory and neural networks, from detailed models of single neurons, analyses of different biological neural networks and connectionist studies of psychology and language to mathematical analyses of a variety of abstract neural networks and technological applications of adaptive, artificial neural networks. The main part of the text, Part Three, contains 267 articles by leaders in the various fields, arranged alphabetically by title. The first two parts are designed to help readers orient themselves to this vast range of material. Part One introduces several basic neural models, explains how the present study of brain theory and neural networks integrates brain theory, artificial intelligence and cognitive psychology, and provides a tutorial on the concepts essential for understanding neural networks as dynamic, adaptive systems. Part Two provides entry into the many articles of Part Three through an introductory "Meta-Map" and 23 road maps, each of which tours all the Part Three articles on the chosen theme.

Table of Contents

  • Part 1 Background: how to use part 1
  • introducing the neuron
  • levels and styles of analysis
  • dynamics and adaptation in neural networks. Part 2 Road maps: the meta-map
  • connectionism - psychology, linguistics and artificial intelligence
  • dynamics, self-organization and cooperativity
  • learning in artificial neural networks
  • applications and implementations
  • biological neurons and networks
  • sensory systems
  • plasticity in development and learning
  • motor control. Part 3 Articles. (Part contents).

by "Nielsen BookData"

Details

Page Top