Title :
Syntax satisfaction for large scale neural networks
Author :
Flake, Gary William
Author_Institution :
Dept. of Comput. Sci., Clemson Univ., SC, USA
Abstract :
Discusses the development of large-scale neural networks and the methods needed to achieve feasible solutions. It is shown that existing tools and techniques for setting parameters, such as external input and neural connectivity hold for large neural networks. This is illustrated by a simulation of a neural network consisting of more than 500000 neurons that has successfully generated permutation matrices
Keywords :
neural nets; external input; large scale neural networks; neural connectivity; neural networks; setting parameters; syntax satisfaction; Analog computers; Biology computing; Computational modeling; Computer networks; Intelligent networks; Joining processes; Large-scale systems; Neural networks; Neurons; Resistors;
Conference_Titel :
Southeastcon '89. Proceedings. Energy and Information Technologies in the Southeast., IEEE
Conference_Location :
Columbia, SC
DOI :
10.1109/SECON.1989.132320
