Convergence analysis of the nontrivial stationary solution of the memristor-based neural networks with reaction-diffusion terms

被引:0
|
作者
Wang, Helin [1 ]
Jiang, Xinrui [1 ]
Qin, Sitian [1 ]
Zhang, Wei [2 ]
Feng, Yuming [2 ]
机构
[1] Harbin Inst Technol, Dept Math, Weihai, Peoples R China
[2] Chongqing Three Gorges Univ, Sch Comp Sci & Engn, Chongqing, Peoples R China
关键词
memristor-based; reaction-diffusion terms; nontrivial solution; Leary-Schauder alternative theorem; TO-STATE STABILITY;
D O I
10.1109/ICACI58115.2023.10146155
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper considers the convergence and existence problem for the nontivial stationary solution of a memristor-based neural network with reaction-diffusion(MNNs). We address the existence of the nontrivial stationary solution by investigating a compact operator whose fixed point is exactly the stationary solution through the Leary-Schauder theorem. Then, under some mild conditions, a lyapounov function is proposed to prove the convergence of the stationary solution. Numerial examples are provided to support the effectiveness of the conclusions.
引用
收藏
页数:8
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