Bifurcations due to different delays of high-order fractional neural networks

Author:

Huang Chengdai1ORCID,Cao Jinde23

Affiliation:

1. School of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, P. R. China

2. School of Mathematics, Southeast University, Nanjing 210096, P. R. China

3. Yonsei Frontier Lab, Yonsei University, Seoul 03722, South Korea

Abstract

This paper expounds the bifurcations of two-delayed fractional-order neural networks (FONNs) with multiple neurons. Leakage delay or communication delay is viewed as a bifurcation parameter, stability zones and bifurcation conditions with respect to them are commendably established, respectively. It declares that both leakage delay and communication delay immensely influence the stability and bifurcation of the developed FONNs. The explored FONNs illustrate superior stability performance if selecting a lesser leakage delay or communication delay, and Hopf bifurcation generates once they overstep their critical values. The verification of the feasibility of the developed analytic results is implemented via numerical experiments.

Funder

Key Scientific Research Project of Colleges and Universities in Henan Province

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Modelling and Simulation

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