New Criteria for Dissipativity Analysis of Fractional-Order Static Neural Networks

被引：0
|
作者：
Duong Thi Hong
Nguyen Huu Sau
Mai Viet Thuan
机构：
[1] TNUS–University of Sciences,Department of Mathematics and Informatics
[2] Hanoi University of Industry,Faculty of Fundamental Science
来源：
Circuits, Systems, and Signal Processing | 2022年 / 41卷
关键词：
Fractional-order static neural networks; Generalized fractional-order neural networks; Asymptotic stable; Dissipativity analysis; Linear matrix inequalities; Convex Lyapunov function; 34D10; 93D15; 49M7; 34K20;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper deals with the dissipativity analysis problem for a class of fractional-order static neural networks (FOSNNs). We first derive a novel sufficient condition for global asymptotic stability of FOSNNs by constructing novel convex Lyapunov functions and using linear matrix inequality techniques. Then, based on the proposed stable criterion combined with some auxiliary properties of fractional calculus, the dissipative problem for the related system is solved for the first time. In addition, we also extend the obtained results to generalized fractional-order neural networks. Four numerical examples are provided to show the validity and effectiveness of the proposed results.
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页码：2221 / 2243
页数：22
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