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Associative Neural Memories : Theory and Implementation - Mohamad H. Hassoun

Associative Neural Memories

Theory and Implementation

By: Mohamad H. Hassoun (Editor)

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Associative neural memories--a class of artificial neural networks--are among the most extensively studied and best understood neural paradigms. This volume brings together pioneering work on associative neural memory and hardware implementation by leading international researchers. The first part describes associative neural models that have close connections to biological or psychological aspects of memory, and demonstrates the important contributions that neurobiology can make to the design of artificial neural networks. Subsequent parts of the book present more complex extensions of the simple memory models, studying their recall capabilities, analyzing various characteristics-- such as capacity, convergence dynamics, and fault tolerance--and describing the hardware implementation of such memories. This book will be of interest to computer science professionals and students as well as to cognitive scientists interested in neural networks.

Industry Reviews

"This wide-ranging book delivers precisely what it clearly promises." --Simulator Quarterly "Some of the papers will be cited as reference for many years to come....The single most important book for the applied neural networks community that I reviewed in this group. Neural networkers will want to read this collection from cover to cover." --Philip Chapnick, AI Expert "This volume brings together significant papers on associative neural memory theory (architecture, learning, analysis, and design) and hardware implementation (VLSI and opto-electronic) by leading international researchers."--Quarterly of Applied Mathematics

Introduction 1: M.H. Hassoun: Dynamic Associative Neural Memories PART I: Biological and Psychological Connections 2: A.L. Alkon, K.T. Blackwell, T.P. Vogl, and S. Werness: Biological Plausibility of Artificial Neural Networks 3: P. Kanerva: Sparse Distributed Memory and Related Models 4: J. Anderson: The BSB Model: A Simple Non-Linear Autoassociative Neural Network PART II: Artificial Associative Neural Memory Models 5: Y-F. Wang, J.B. Cruz Jr., and J.H. Mulligan, Jr.: Bidirectional Associative Memories 6: A. Dembo: High Density Associative Memories 7: B. Baird and F. Eeckman: A Normal Form Projection Algorithm for Associative Memory PART III: Analysis of Memory Dynamics and Capacity 8: S-I. Amari and H-F. Yanai: Statistical Neurodynamics of Various Types of Associative Nets 9: J. Komlos and R. Paturi: Convergence Analysis of Associative Memories 10: C.M. Marcus, F.R. Waugh and R.M. Westervelt: Nonlinear Dynamics of Analog Associative Memories 11: S. Hui et al.: Dynamics and Stability Analysis of the Brain-State-in-a-Box BSB Neural Model 12: G. Pancha and S.S. Venkatesh: Feature and Memory Selective Error Correction in Neural Associative Memory 13: S. Yoshizawa, M. Morita and S-I. Amari: Analysis of Dynamics and Capacity of Associative Memory Using a Non-Monotonic Neuron Model 14: P-C. Chung and T.F. Krile: Fault-Tolerance of Optical and Electronic Hebbian-Type Associative Memories PART IV: Implementation 15: M. Verleysen, J.D. Legat and P.G.A. Jespers: Analog Implementation of an Associative Memory 16: T-D. Chiueh and R.M. Goodman: Recurrent Correlation Associative Memories and Their VSLI Implementation 17: K.A. Bohen and A.G. Andreou: Design of a Bidirectional Associative Memory Chip 18: F.T.S. Yu: Optical Implementation of Programmable Associative Memories 19: K. Kyuma, J. Ohta and Y. Nitta: Optical Learning Neurochips for Pattern Recognition, Classification, and Association Index

ISBN: 9780195076820
ISBN-10: 0195076826
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 372
Published: 12th August 1993
Country of Publication: US
Dimensions (cm): 23.0 x 16.0  x 3.18
Weight (kg): 0.95