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. ...
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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.
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Seller's Description:
Good. A copy that has been read, but remains in clean condition. All pages are intact, and the cover is intact (including dust cover, if applicable). The spine may show signs of wear. Pages can include limited notes and highlighting, and the copy can include "From the library of" labels or limited small stickers. Book may have a remainder mark or be a price cutter. A CLEAN COPY WITH A SLIGHTLY WORN COVER.
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Seller's Description:
Textual graphs & tables. Minor rubbing. Light page-edge & binding soil. VG. 24x17cm, xxi, 350 pp. Contains 19 papers. Includes: M.A. Hassoun "Dynamic Associative Neural Memories"; D.L. Alkon; et al: "Biological Plausibility of Artificial Neural Networks: Learning by Non-Hebbian Synapses"; P. Kanerva "Sparse Distributed Memory & Related Models"; J.A. Anderson "The BSB Model: A Simple Nonlinear Autoassociative Neural Network"; Y. -F. Wang " Bidirectional Associative Memories"; A. Dembo "High-Density Associative Memories"; B. Baird & F. Eeckman "A Normal Form Projection Algorithm for Associative Memory"; S. -I. Amari & H. -F. Yanai "Statistical Neurodynamics of Various Types of Associative Nets"; R. Paturi "Convergence Analysis of Associative Memories"; F.R. Waugh; et al: "Nonlinear Dynamics of Analog Associative Memories"; S. Hui; et al: "Dynamics & Stability Analysis of the Brain-State-in-a-Box (BSB) Neural Models"; G. Pancha & S.S. Venkatesh "Feature & Memory-Selective Error Correction in Neural Associative Memory"; S. Yoshizawa; et al: " Analysis of Dynamics & Capacity of Associative Memory Using a Nonmonotonic Neuron Model"; P. -C. Chung & T.F. Krile "Fault-Tolerance of Optical & Electronic Hebbian-type Associative Memories"; M. Verleysen; et al: "Analog Implementation of an Associative Memory: Learning Algorithm & VLSI Constraints"; T. -D. Chiueh & R.M. Goodman " Recurrent Correlation Associative Memories & their VLSI Implementation"; K.A. Boahen & A. G, . Andreou "Design of a Bidirectional Associative Memory Chip"; F.T.S. Yu "Optical Implementation of Programmable Associative Memories"; etc.
