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
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
I have taken this program and I highly recommend it to all health-care providers - Orville R. Weyrich, Jr PhD NMD.
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