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Bifurcation Mechanism for Fractional-Order Three-Triangle Multi-delayed Neural Networks.

Authors :
Xu, Changjin
Liu, Zixin
Li, Peiluan
Yan, Jinling
Yao, Lingyun
Source :
Neural Processing Letters; Oct2023, Vol. 55 Issue 5, p6125-6151, 27p
Publication Year :
2023

Abstract

This article is basically concerned with the stability and Hopf bifurcation problem of fractional-order three-triangle multi-delayed neural networks. Based on laplace transform, we obtain the characteristic equation of the considered fractional-order three-triangle multi-delayed neural networks. By discussing the distribution of the roots for the characteristic equation, the delay-independent stability condition and delay-induced bifurcation criterion are built. The research manifests that time delay is an important factor which affects the stability and the onset of Hopf bifurcation for fractional-order three-triangle multi-delayed neural networks. The computer simulation results and bifurcation figures are displayed to support the established main conclusions. The derived fruits of this article have great theoretical values in dominating neural networks. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13704621
Volume :
55
Issue :
5
Database :
Complementary Index
Journal :
Neural Processing Letters
Publication Type :
Academic Journal
Accession number :
172445331
Full Text :
https://doi.org/10.1007/s11063-022-11130-y