Exploration on bifurcation for an incommensurate five-neuron fractional-order BAM neural network involving multiple delays

被引:7
作者
Zhang, Yanxia [1 ,2 ]
Li, Long [1 ]
Huang, Junjian [3 ]
Gorbachev, Sergey [4 ]
Aravind, R. Vijay [4 ]
机构
[1] Chongqing Univ Educ, Sch Math & Big Data, Chongqing 400065, Peoples R China
[2] Chongqing Normal Univ, Sch Math Sci, Chongqing 401331, Peoples R China
[3] Southwest Univ, Coll Elect & Informat Engn, Chongqing 400715, Peoples R China
[4] Chongqing Univ Educ, Sch Artificial Intelligence, Chongqing 400065, Peoples R China
关键词
BAM neural network; Fractional-order; Delays; Bifurcation; HOPF-BIFURCATION; 2-NEURON NETWORK; STABILITY; DISCRETE;
D O I
10.1016/j.physd.2023.134047
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Some qualitative analyses of bifurcations for an incommensurate fractional -order neural network with delays are considered. At first, we display an incommensurate five -neuron fractional -order bidirectional associative memory neural network (FOBAMNN) with four delays. Next, the existence and uniqueness of the solution are analyzed. Afterward, from the perspective of the two different cases of delays inducing bifurcations, some sufficient criteria of the stability and the occurrence of Hopf bifurcation are established. Some numerical simulations are designed to verify the feasibility and validity of the obtained theorems. In addition, the effects of the delays on the stability and bifurcation of the integer -order neural network and the fractional -order neural network are discussed and some meaningful results are presented in the end.
引用
收藏
页数:20
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