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

Authors :
Huang, Chengdai
Cao, Jinde
Source :
International Journal of Biomathematics. Feb2022, Vol. 15 Issue 2, p1-19. 19p.
Publication Year :
2022

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. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
*HOPF bifurcations
*LEAKAGE

Details

Language :
English
ISSN :
17935245
Volume :
15
Issue :
2
Database :
Academic Search Index
Journal :
International Journal of Biomathematics
Publication Type :
Academic Journal
Accession number :
155344501
Full Text :
https://doi.org/10.1142/S1793524521500753