Author : Y C Lee
Publisher : World Scientific
Page : 424 pages
File Size : 46,5 Mb
Release : 1989-01-01
Category : Computers
ISBN : 9789814522083
Evolution, Learning and Cognition by Y C Lee Pdf
This review volume represents the first attempt to provide a comprehensive overview of this exciting and rapidly evolving development. The book comprises specially commissioned articles by leading researchers in the areas of neural networks and connectionist systems, classifier systems, adaptive network systems, genetic algorithm, cellular automata, artificial immune systems, evolutionary genetics, cognitive science, optical computing, combinatorial optimization, and cybernetics. Contents:Connectionist Learning Through Gradient Following (R J Williams)Efficient Stochastic Gradient Learning Algorithms for Neural Networks (Y C Lee)Information Storage in Fully Connected Networks (D Psaltis & S S Venkatesh)Neuronic Equations and their Solutions (E R Caianiello)The Dynamics of Searches Directed by Genetic Algorithms (J H Holland)Probabilistic Neural Networks (J W Clark)Some Quantitative Issues in the Theory of Perception (A Zee)Speech Perception and Production by a Self-Organising Neural Network (M A Cohen et al.)Neocognitron: A Neural Network Model for Visual Pattern Recognition (K Fukushima et al.)Learning to Predict the Secondary Structure of Globular Proteins (N Qian & T J Sejnowski)Exploiting Chaos to Predict the Future and Reduce Noise (J D Farmer & J J Sidorowich)How Neural Nets Work (A Lapedes & R Farber)Pattern Recognition and Single Layer Networks (T Maxwell)What is the Significance of Neural Networks for AI? (H H Szu)Selected Bibliography on Connectionism (O G Selfridge et al.) Readership: Computer scientists, applied mathematicians, physicists, biologists, cognitive scientists, microelectronic engineers, genetic scientists, engineers and artificial intelligence researchers.