Title :
VLSI implementation of a fully parallel stochastic neural network
Author :
Quero, J.M. ; Ortega, J.G. ; Janer, C.L. ; Franquelo, L.G.
Author_Institution :
Dept. de Ingenieria de Sistemas y Automatica, Seville Univ., Spain
fDate :
27 Jun-2 Jul 1994
Abstract :
Presents a purely digital stochastic implementation of multilayer neural networks. The authors have developed this implementation using an architecture that permits the addition of a very large number of synaptic connections, provided that the neuron´s transfer function is the hard limiting function. The expression that relates the design parameter, that is, the maximum pulse density, with the accuracy of the operations has been used as the design criterion. The resulting circuit is easily configurable and expandable
Keywords :
VLSI; neural chips; neural net architecture; VLSI implementation; design parameter; fully parallel stochastic neural network; maximum pulse density; multilayer neural networks; transfer function; Arithmetic; Counting circuits; Hardware; Multi-layer neural network; Neural networks; Neurons; Pulse generation; Stochastic processes; Transfer functions; Very large scale integration;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374527