Description
Key Features * 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 * Applications to finite constraint problems * Practical realization methods for Hebbian type associative memory systems * Parallel self-organizing hierarchical neural network systems * Dynamics of networks of biological neurons for utilization in computational neuroscience Practitioners, researchers, and students in industrial, manufacturing, electrical, and mechanical engineering, as well as in computer science and engineering, will find this volume a unique and comprehensive reference to a broad array of algorithms and architectures
About the Author
Cornelius T. Leondes received his B.S., M.S., and Ph.D. from the University of Pennsylvania and has held numerous positions in industrial and academic institutions. He is currently a Professor Emeritus at the University of California, Los Angeles. He has also served as the Boeing Professor at the University of Washington and as an adjunct professor at the University of California, San Diego. He is the author, editor, or co-author of more than 100 textbooks and handbooks and has published more than 200 technical papers. In addition, he has been a Guggenheim Fellow, Fulbright Research Scholar, IEEE Fellow, and a recipient of IEEE's Baker Prize Award and Barry Carlton Award.
Book Information
ISBN 9780124438613
Author Cornelius T. Leondes
Format Hardback
Page Count 460
Imprint Academic Press Inc
Publisher Elsevier Science Publishing Co Inc
Weight(grams) 840g