Pulsed Neural Networks (Bradford Books)
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Pulsed Neural Networks (Bradford Books) Overview
Most practical applications of artificial neural networks are based on a computational model involving the propagation of continuous variables from one processing unit to the next. In recent years, data from neurobiological experiments have made it increasingly clear that biological neural networks, which communicate through pulses, use the timing of the pulses to transmit information and perform computation. This realization has stimulated significant research on pulsed neural networks, including theoretical analyses and model development, neurobiological modeling, and hardware implementation.This book presents the complete spectrum of current research in pulsed neural networks and includes the most important work from many of the key scientists in the field. Terrence J. Sejnowski's foreword, "Neural Pulse Coding," presents an overview of the topic. The first half of the book consists of longer tutorial articles spanning neurobiology, theory, algorithms, and hardware. The second half contains a larger number of shorter research chapters that present more advanced concepts. The contributors use consistent notation and terminology throughout the book.Contributors : Peter S. Burge, Stephen R. Deiss, Rodney J. Douglas, John G. Elias, Wulfram Gerstner, Alister Hamilton, David Horn, Axel Jahnke, Richard Kempter, Wolfgang Maass, Alessandro Mortara, Alan F. Murray, David P. M. Northmore, Irit Opher, Kostas A. Papathanasiou, Michael Recce, Barry J. P. Rising, Ulrich Roth, Tim Schönauer, Terrence J. Sejnowski, John Shawe-Taylor, Max R. van Daalen, J. Leo van Hemmen, Philippe Venier, Hermann Wagner, Adrian M. Whatley, Anthony M. Zador.
Pulsed Neural Networks (Bradford Books) Specifications
Traditional neural network computing uses continuous propagation of its signals, whereas biological networks use signal timing and frequency in their transmission and computation. Pulsed Neural Networks arose out of a two-day workshop at the Isaac Newton Institute for Mathematical Studies at Cambridge, and provides a broad overview of the comparatively recent developments in building and working with these machines.
A compelling foreword by Terrence J. Sejnowski explains the basics. Several tutorial chapters covering biological and electronic pulsed computing follow. The rest of the book is divided into two parts: "Implementations" and "Design and Analysis of Pulsed Neural Systems."
Useful for neuroscientists, engineers, and, of course, computer scientists, Pulsed Neural Networks requires a certain familiarity with traditional neural networks and demands a willingness to probe neurobiological theory. However, this text rewards readers for their hard work with a much more powerful and robust approach to the problems of neural computing. --Rob Lightner
