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.

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

"This wide-ranging book delivers precisely what it clearly promises." --Simulator Quarterly |k No