Synchronization of Fractional Order Fuzzy BAM Neural Networks With Time Varying Delays and Reaction Diffusion Terms

被引：28

作者：

Ali, M. Syedy ^{[1
]}

Hymavathi, M. ^{[1
]}

Rajchakit, Grienggrai ^{[2
]}

Saroha, Sumit ^{[3
]}

Palanisamy, L. ^{[1
]}

Hammachukiattikul, Porpattama ^{[4
]}

机构：

[1] Thiruvalluvar Univ, Dept Math, Vellore 632115, Tamil Nadu, India

[2] Maejo Univ, Dept Math, Fac Sci, Chiang Mai 50290, Thailand

[3] Guru Jambheshwar Univ Sci & Technol, Dept Printing Technol Elect Engn, Hisar 125011, Haryana, India

[4] Phuket Rajabhat Univ PKRU, Dept Math, Fac Sci, Phuket 83000, Thailand

来源：

IEEE ACCESS | 2020年 / 8卷

关键词：

Delays; Asymptotic stability; Stability analysis; Biological neural networks; Mathematics; Delay effects; Synchronization; time varying delays; reaction diffusion; STABILITY; CALCULUS; SYSTEMS;

D O I：

10.1109/ACCESS.2020.3029145

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this article synchronization of fractional order fuzzy BAM neural networks with time varying delays and reaction diffusion terms is studied. The time varying delays consist of discrete delays and distributed delays are considered. Then, some sufficient conditions black are presented to guarantee the global asymptotic stability of the error system by using Lyapunov-Krasovskii functional having the double integral terms, we utilized Jensens inequality techniques and LMI approach. Accordingly, we accomplished synchronization of master-slave fuzzy BAMNNs. The delay dependent stability conditions are set up in terms of linear matrix inequalities(LMIs), which can be productively understood utilizing Matlab LMI control tool box. At last, illustrative numerical results have been provided to verify the correctness and effectiveness of the obtained results.

引用

页码：186551 / 186571

页数：21

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