New criteria for finite-time stability of fractional order memristor-based neural networks with time delays

被引：0
|
作者：
Du F. [1 ,2 ]
Lu J.-G. [1 ,2 ]
机构：
[1] Department of Automation, Shanghai Jiao Tong University, Shanghai
[2] Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai
来源：
Neurocomputing | 2021年 / 421卷
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Finite-time stability; Fractional order; Memristor; Neural network; Time delay;
D O I：
10.1016/j.neucom.2020.09.039
中图分类号：
学科分类号：
摘要：
In this paper, the finite-time stability (FTS) problems for a class of fractional order memristor-based neural network (FOMNN) with time delays are investigated. Based on the method of steps, set-valued mapping, the theory of differential inclusion and fractional order Gronwall inequality, a new delay dependent criterion for the FTS of FOMNN with time delays and the fractional order 0<μ<1 is derived, which is less conservative than the existing criteria. Furthermore, a sufficient condition to ensure the FTS of FOMNN with the fractional-order 1<μ<2 is proposed. Finally, two examples are given to illustrate the validity of the proposed results. © 2020 Elsevier B.V.
引用
收藏
页码：349 / 359
页数：10
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