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S-Asymptotically ω-Periodic Solutions of Fractional-Order Complex-Valued Recurrent Neural Networks With Delays
被引:5
|作者:
Hou, Yuanyuan
[1
]
Dai, Lihua
[2
]
机构:
[1] Puer Univ, Dept Math & Stat, Puer 665000, Peoples R China
[2] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China
来源:
关键词:
Fractional-order derivative;
S-asymptotically omega-periodic solution;
Mittag-Lef~er function;
complex-valued neural network;
synchronization;
STABILITY ANALYSIS;
GLOBAL STABILITY;
SYNCHRONIZATION;
D O I:
10.1109/ACCESS.2021.3063746
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 paper, we consider the problem of the S-asymptotically omega-periodic synchronization of fractional-order complex-valued recurrent neural networks with time delays. Firstly, we can not explicitly decompose the fractional-order complex-valued systems into equivalent fractional-order real-valued systems, by means of the contraction mapping principle and some important features of Mittag-Leffler functions, we obtain some sufficient conditions for the existence and uniqueness of S-asymptotically omega-periodic solutions for this class of neural networks. Then, by constructing an appropriate Lyapunov functional, the theory of fractional differential equation, and some inequality techniques, sufficient conditions are obtained to guarantee the global Mittag-Leffler synchronization of the drive-response systems. Finally, two examples are given to illustrate the effectiveness and feasibility of our main results.
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页码:37883 / 37893
页数:11
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