Finite-time stability for memristor based switched neural networks with time-varying delays via average dwell time approach

被引：38

作者：

Ali, M. Syed ^{[1
]}

Saravanan, S. ^{[1
]}

机构：

[1] Thiruvalluvar Univ, Dept Math, Vellore 632115, Tamil Nadu, India

来源：

NEUROCOMPUTING | 2018年 / 275卷

关键词：

Average dwell time approach; Finite-time stability; Lyapunov-Krasovskii functional; Memristor; Switched neural networks; ROBUST EXPONENTIAL STABILITY; STABILIZATION; SYNCHRONIZATION; SYSTEMS;

D O I：

10.1016/j.neucom.2017.10.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we investigated the problem of the finite-time stability for a class of memristor based switched neural networks with time-varying delays. By constructing proper Lyapunov functionals. Based on the average dwell time technique, mode-dependent average dwell time technique and using a free-matrix-based integral inequality, Jensen's inequality are used to estimate the upper bound of the derivative of the LKF, several sufficient conditions are given to ensure the finite-time stability of the memristor-based switched neural networks with discrete and distributed delays in the sense of feasible solutions. The finite-time stability conditions here are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. Finally, the numerical examples are provided to verify the effectiveness and benefit of the proposed criterion. (c) 2017 Elsevier B.V. All rights reserved.

引用

页码：1637 / 1649

页数：13

共 47 条

[1] Finite-time synchronization for memristor-based neural networks with time-varying delays [J].

Abdurahman, Abdujelil ;

Jiang, Haijun ;

Teng, Zhidong .

NEURAL NETWORKS, 2015, 69 :20-28

[2] Approximate Solutions of DASs with Nonclassical Boundary Conditions using Novel Reproducing Kernel Algorithm [J].

Abu Arqub, Omar .

FUNDAMENTA INFORMATICAE, 2016, 146 (03) :231-254

[3] The reproducing kernel algorithm for handling differential algebraic systems of ordinary differential equations [J].

Abu Arqub, Omar .

MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2016, 39 (15) :4560-4573

[4] Numerical solution of systems of second-order boundary value problems using continuous genetic algorithm [J].

Abu Arqub, Omar ;

Abo-Hammour, Zaer .

INFORMATION SCIENCES, 2014, 279 :396-415

[5] Finite-time stability of continuous autonomous systems [J].

Bhat, SP ;

Bernstein, DS .

SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2000, 38 (03) :751-766

[6] Finite-time stabilization control of memristor-based neural networks [J].

Cai, Zuowei ;

Huang, Lihong ;

Zhu, Mingxun ;

Wang, Dongshu .

NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2016, 20 :37-54

[7] Global exponential almost periodicity of a delayed memristor-based neural networks [J].

Chen, Jiejie ;

Zeng, Zhigang ;

Jiang, Ping .

NEURAL NETWORKS, 2014, 60 :33-43

[8] Finite time stability of periodic solution for Hopfield neural networks with discontinuous activations [J].

Chen, Xiaoyan ;

Huang, Lihong ;

Guo, Zhenyuan .

NEUROCOMPUTING, 2013, 103 :43-49

[9] MEMRISTOR - MISSING CIRCUIT ELEMENT [J].

CHUA, LO .

IEEE TRANSACTIONS ON CIRCUIT THEORY, 1971, CT18 (05) :507-+

[10] Nonlinear Dynamics of Memristor Oscillators [J].

Corinto, Fernando ;

Ascoli, Alon ;

Gilli, Marco .

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2011, 58 (06) :1323-1336

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