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. For more information, see: The CSI Report and Video and Become a New Patient Magnet |