Introduction to the Theory of Neural Computation; A Lecture Notes Volume in the Santa Fe Institute...

Abstract: A comprehensive introduction to neural network models being studied for computational applications.

Keywords: book review, robotics, psychology, ai, programming, cognition, associative memory, feed forward networks, unsupervised learning, pattern recognition, optimization, neurobiology, neural computers.

Title: Introduction to the Theory of Neural Computation; A Lecture Notes Volume in the Santa Fe Institute... Author: John A. Hertz, Richard G. Palmer, Anders Krogh Publisher: Addison-Wesley Date Published: January 1991 ISBN: 0201515601 LOCN: QA76.5.H475 1991 Dewey: 006.3 20 Pages: 327 Bibliography: 432 entries Figures: 108

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CONTENTS

Foreword

Preface

Chapter 1: Introduction

Chapter 2: The Hopfield Model

Chapter 3: Extensions of the Hopfield Model

Chapter 4: Optimization Problems

Chapter 5: Simple Perceptrons

Chapter 6: Multi-Layer Networks

Chapter 7: Recurrent Networks

Chapter 8: Unsupervised Hebbian Learning

Chapter 9: Unsupervised Competitive Learning

Chapter 10: Formal Statistical Mechanics of Neural Networks

Appendix : Statistical Mechanics

LIBRARY OF CONGRESS DATA

Author:        Hertz, John.
Title:         Introduction to the theory of neural computation
                  / John Hertz, Anders Krogh, Richard G. Palmer.
Published:     Redwood City, Calif. : Addison-Wesley Pub. Co.,
                  c1991.
Description:   xxii, 327 p. : ill. ; 25 cm.
Series:        Santa Fe Institute studies in the sciences of
                  complexity. Lecture notes ; v. 1
LC Call No.:   QA76.5.H475 1991
Dewey No.:     006.3 20
ISBN:          0201503956
               0201515601 (pbk.)
Notes:         Includes bibliographical references (p. 281-306)
                  and indexes.
Subjects:      Neural computers.
               Neural networks (Neurobiology)
Other authors: Krogh, Anders.
               Palmer, Richard G.
Control No.:   90000701 //r93

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