Algorithms and Architectures

Series Editor:

  • Cornelius Leondes, University of California, Los Angeles, U.S.A.


  • Cornelius Leondes, University of California, Los Angeles, U.S.A.

This volume is the first diverse and comprehensive treatment of algorithms and architectures for the realization of neural network systems. It presents techniques and diverse methods in numerous areas of this broad subject. The book covers major neural network systems structures for achieving effective systems, and illustrates them with examples.This volume includes Radial Basis Function networks, the Expand-and-Truncate Learning algorithm for the synthesis of Three-Layer Threshold Networks, weight initialization, fast and efficient variants of Hamming and Hopfield neural networks, discrete time synchronous multilevel neural systems with reduced VLSI demands, probabilistic design techniques, time-based techniques, techniques for reducing physical realization requirements, and applications to finite constraint problems.A unique and comprehensive reference for a broad array of algorithms and architectures, this book will be of use to practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering.
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Practitioners, research workers, academics, and students in mechanical, electrical, industrial, manufacturing, and production engineering, as well as computer science and engineering.


Book information

  • Published: October 1997
  • ISBN: 978-0-12-443861-3

Table of Contents

Freeman, Orr, and Saad, Statistical Theories of Learning in Radial Basis Function Networks. Kim, Park, Oh, and Han, The Synthesis of Three-Layer Threshold Networks. Lehtokangas, Salmela, Saarinen, and Kaski, Weight Initialization Techniques. Meilijson, Ruppin, and Sipper, Fast Computation in Hamming and Hopfield Networks. Si and Michel, Multilevel Neurons. Watanabe and Fukumizu, Probabilistic Design. Tom and Tenorio, Short Time Memory Problems. Chung and Tsai, Reliability Issue and Quantization Effects in Optical and Electronic Network Implementations of Hebbian-Type Associative Memories. Monfroglio, Finite Constraint Satisfaction. Chu, Estimating the Dimensions of Manifolds Using Delaunay Diagrams. Ersoy, Parallel, Self-Organizing, Hierarchical Neural Network Systems. Subject Index.