NOVEL RESULTS ON BIFURCATIONS FOR A FRACTIONAL-ORDER NEURAL NETWORK WITH NEUTRAL DELAYS

Chengdai Huang, Shansong Mo and Zengbao Wu
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Chengdai Huang: School of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, P. R. China
Shansong Mo: School of Mathematics and Statistics, Xinyang Normal University, Xinyang 464000, P. R. China
Zengbao Wu: School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, P. R. China

FRACTALS (fractals), 2022, vol. 30, issue 06, 1-16

Abstract: In comparison with numerous available results with regard to bifurcations on account of fractional-order neural networks (FONNs) with the retarded delays, this paper is concerned with the stability and bifurcation of FONN with neutral delays. Delay-induced bifurcation results are firstly, procured and the bifurcation diagrams with respect to different delays are nicely plotted. Then it reveals that both time delay and fractional order have important effects in affecting the stability and bifurcation of the developed FONN. It further detects that FONN involving neutral delays can postpone the onset of bifurcations of the developed FONN compared with FONN with the retarded delays. It hints that neutral delays have a vital impact on the dynamics of FONNs in comparison with FONN with the retarded delays, which has outstanding performance in maintaining stability of FONNs. Eventually, numerical examples are addressed to check the availability of the developed results. The obtained criterion can be evaluated as an important contribution to the stability issue of the considered neural networks (NNs).

Keywords: Stability; Hopf Bifurcation; Neutral Delay; Retarded Delay; Fractional-Order Neural Networks (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X22501183

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