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

被引：9
|
作者：
Duong Thi Hong [1 ]
Nguyen Huu Sau [2 ]
Mai Viet Thuan [1 ]
机构：
[1] TNUS Univ Sci, Dept Math & Informat, Thainguyen, Vietnam
[2] Hanoi Univ Ind, Fac Fundamental Sci, 298 Cau Dien St, Hanoi, Vietnam
来源：
CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2022年 / 41卷 / 04期
关键词：
Fractional-order static neural networks; Generalized fractional-order neural networks; Asymptotic stable; Dissipativity analysis; Linear matrix inequalities; Convex Lyapunov function; TIME-VARYING DELAYS; STABILITY ANALYSIS; EXTENDED DISSIPATIVITY; EXPONENTIAL STABILITY; INTERVAL; SYSTEM; PASSIVITY;
D O I：
10.1007/s00034-021-01888-2
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
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.
引用
收藏
页码：2221 / 2243
页数：23
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