Chaotic invariant sets of a delayed discrete neural network of two non-identical neurons

Chen, YuanLong; Yu, Huan; Zou, Xingfu

doi:10.1007/s11425-013-4640-y

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Cited by 8 publications

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“…Recently, Huang and Zou in [8] showed the discrete network system consisting of two identical neurons with a uniform delay demonstrates snapback repeller chaotic behaviors near an equilibrium point. For the Hopfield networks with two different neurons [9][10][11], the conditions that the systems exhibit chaos are obtained. In [12], Wu et al analyzed the chaotic behaviors of the parameterized discrete dynamics of recurrent m-neuron networks evoked by external inputs and obtained some conditions which the subsystem is topologically conjugate to symbolic dynamical system.…”

Section: Introductionmentioning

confidence: 99%

Chaos on Discrete Neural Network Loops with Self-Feedback

Chen

2020

Discrete Dynamics in Nature and Society

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In this paper, the complex dynamical behaviors in a discrete neural network loop with self-feedback are studied. Specifically, an invariant closed set of the system of neural network loops is built and the subsystem restricted on this invariant closed set is topologically conjugate to a two-sided symbolic dynamical system which has two symbols. In the end, some illustrative numerical examples are given to demonstrate our theoretical results.

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