THE LENGTH OF ATTRACTORS IN ASYMMETRIC RANDOM NEURAL NETWORKS WITH DETERMINISTIC DYNAMICS

NUTZEL, K (1991) THE LENGTH OF ATTRACTORS IN ASYMMETRIC RANDOM NEURAL NETWORKS WITH DETERMINISTIC DYNAMICS. [["eprint_typename_letter" not defined]]

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Abstract

I have developed a method to detect attractors of any length in large neural networks with up to 1024 neurons within a reasonable period of CPU time. In networks with symmetric couplings only stable states and, in the case of parallel dynamics, cycles of length 2 exist. The presented simulations suggest that, in sufficiently large systems, this holds also for couplings up to a distinct value of asymmetry. Beyond this value extremely long cycles are detected and the average cycle length depends exponentially on system size.

Item Type:	["eprint_typename_letter" not defined]
Uncontrolled Keywords:	GLAUBER DYNAMICS; SYSTEMS; BONDS;
Depositing User:	Dr. Gernot Deinzer
Last Modified:	19 Oct 2022 08:46
URI:	https://pred.uni-regensburg.de/id/eprint/55086

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