This book is a vivid presentation of the foremost research and theory from the disciplines that provide the foundations of neural network research: neurobiology, physics, computer science, electrical engineering, mathematics, and psychology. An Introduction to Neural and Electronic Networks, Second Edition shows how neural networks and neurocomputing represent radical departures from conventional approaches to digital computers, in terms of algorithms as well as architecture. This Second Edition contains new chapters on computational models of hippocampal and cerebellar function, nonlinear information processing, adaptive filtering and pattern recognition, and digital VLSI architecture. Its strong interdisciplinary emphasis will appeal to a wide array of researchers and students - from neurobiologists to psychologists.

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* Written by the leading researchers in neural networks

* Provides an intermediate-level introduction to many important research topics in neuroscience and engineering

* Emphasizes two main areas:

* Computational neuroscience, with coverage of mathematical models of specific regions of the brain, such as the hippocampus, the visual system, the sensory neocortex, and the oflactory cortex

* Engineering hardware models of neural networks, including discussions of VLSI and optical modeling principles, holography, and resistive networks

* Captures the flavor of a successcul interdisciplinary approach to the neural network enterprise

About the Author

Edited by Steven F. Zornetzer, Clifford Lau, Thomas M. McKenna and Joel L. Davis

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