A further study on bifurcation for fractional order BAM neural networks with multiple delays

被引：45

作者：

Xu C. ^{[1
]}

Aouiti C. ^{[2
]}

Liu Z. ^{[3
]}

机构：

[1] Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang

[2] Faculty of Sciences of Bizerta, UR13ES47 Research Units of Mathematics and Applications, University of Carthage, Bizerta

[3] School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guiyang

来源：

Neurocomputing | 2020年 / 417卷

基金：

中国国家自然科学基金;

关键词：

Bifurcation diagram; Boundedness; Existence and uniqueness; Fractional-order BAM neural networks; Hopf bifurcation; Stability;

D O I：

10.1016/j.neucom.2020.08.047

中图分类号：

学科分类号：

摘要：

In the present work, new fractional order BAM neural networks with multiple delays are formulated. Firstly, we study the existence and uniqueness of solution of the constructed neural networks by applying Lipschitz condition. Secondly, the boundedness of solution for the involved neural networks is analyzed by constructing an appropriate function. Thirdly, with the aid of the stability theorem and Hopf bifurcation theory of the fractional order delayed differential systems, the sufficient criterion to guarantee the stability and the existence of Hopf bifurcation for the addressed neural networks is set up. In the end, simulation results are displayed with computer software to support research findings. The established theoretical results of this work have significant theoretical guiding value in dominating and optimizing networks. © 2020 Elsevier B.V.

引用

页码：501 / 515

页数：14

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