Publisher's Synopsis
This is a presentation of research and theory from the disciplines that provide the foundations of neural network research: neurobiology, physics, computer science, electrical engineering, mathematics and psychology. It shows how neural networks and neurocomputing represent radical departures from conventional approaches to digital computers, in terms of algorithms as well as architecture. More than 200 line drawings illustrate the many facets of and approaches to neural networks research. 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 interdisciplinary emphasis is aimed at a wide array of researchers and students - from neurobiologists to psychologists.;This book: is written by the leading researchers in neural networks; provides an intermediate-level introduction to many important research topics in neuroscience and engineering; emphasizes 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 olfactory cortex; and emphasizes engineering hardware models of neural networks, including discussions of VLSI and optical modelling principles, holography and resistive networks.