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Proceedings Paper

Nonlinear dynamics in a neural network (parallel) processor
Author(s): A. G. Unil Perera; S. G. Matsik; S. R. Betarbet
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Paper Abstract

We consider an iterative map derived from the device equations for a silicon p+-n-n+ diode, which simulates a biological neuron. This map has been extended to a coupled neuron circuit consisting of two of these artificial neurons connected by a filter circuit, which could be used as a single channel of a parallel asynchronous processor. The extended map output is studied under different conditions to determine the effect of various parameters on the pulsing pattern. As the control parameter is increased, fixed points (both stable and unstable) as well as a limit cycle appear. On further increase, a Hopf bifurcation is seen causing the disappearance of the limit cycle. The increasing control parameter, which is related to a decrease in the bias applied to the circuit, also causes variation in the location of the fixed points. This variation could be important in applications to neural networks. The control parameter value at which the fixed point appear and the bifurcation occurs can be varied by changing the weightage of the filter circuit. The modeling outputs, are compared with the experimental outputs.

Paper Details

Date Published: 16 June 1995
PDF: 10 pages
Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); doi: 10.1117/12.211986
Show Author Affiliations
A. G. Unil Perera, Georgia State Univ. (United States)
S. G. Matsik, Georgia State Univ. (United States)
S. R. Betarbet, Georgia State Univ. (United States)

Published in SPIE Proceedings Vol. 2488:
Visual Information Processing IV
Friedrich O. Huck; Richard D. Juday, Editor(s)

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