Multistability and instability analysis of recurrent neural networks with time-varying delays

Neural Networks : the Official Journal of the International Neural Network Society
Fanghai Zhang, Zhigang Zeng

Abstract

This paper provides new theoretical results on the multistability and instability analysis of recurrent neural networks with time-varying delays. It is shown that such n-neuronal recurrent neural networks have exactly [Formula: see text] equilibria, [Formula: see text] of which are locally exponentially stable and the others are unstable, where k0 is a nonnegative integer such that k0≤n. By using the combination method of two different divisions, recurrent neural networks can possess more dynamic properties. This method improves and extends the existing results in the literature. Finally, one numerical example is provided to show the superiority and effectiveness of the presented results.

Citations

Mar 21, 2018·Journal of Clinical Monitoring and Computing·Soojin ParkNoemie Elhadad
Nov 8, 2019·Neural Networks : the Official Journal of the International Neural Network Society·Peng WanShuang Jin
Apr 26, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Fanghai ZhangZhigang Zeng
May 18, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Yuanchu ShenShiping Wen

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