Algorithms and ArchitecturesThis 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 ExpandandTruncate Learning algorithm for the synthesis of ThreeLayer 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, timebased 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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Contents
Synthesis of ThreeLayer Threshold Networks  61 
Weight Initialization Techniques  87 
Fast Computation in Hamming and Hopfield Networks  123 
Multilevel Neurons  155 
Probabilistic Design  181 
Short Time Memory Problems  231 
Reliability Issue and Quantization Effects in Optical and Electronic Network Implementations of HebbianType Associative Memories  261 