Finite-time stability analysis of fractional-order memristive fuzzy cellular neural networks with time delay and leakage term

被引：51

作者：

Ali, M. Syed ^{[1
]}

Narayanan, G. ^{[1
]}

Saroha, Sumit ^{[2
]}

Priya, Bandana ^{[3
]}

Thakur, Ganesh Kumar ^{[4
]}

机构：

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

[2] Guru Jambheshwar Univ Sci & Technol, Dept Elect Engn, Hisar, Haryana, India

[3] GL BAJAJ Inst Technol & Management, Dept Appl Sci, Greater Noida, Uttar Pradesh, India

[4] Krishna Engn Coll, Dept Appl Sci, Ghaziabad 201007, UP, India

来源：

MATHEMATICS AND COMPUTERS IN SIMULATION | 2021年 / 185卷

关键词：

Fractional order; Finite-time stability; Fuzzy cellular neural networks(FCNNs); Memristor; Time delay; Leakage term; VARYING DELAYS; EXPONENTIAL STABILITY; LIMIT-CYCLES; MODEL; SYNCHRONIZATION; DISCRETE; STABILIZATION; BIFURCATION; EXISTENCE; EQUATION;

D O I：

10.1016/j.matcom.2020.12.035

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, we investigate finite-time stability analysis of fractional-order memristive fuzzy cellular neural networks(MFFCNNs) with time delay and leakage term. MFFCNNs are formulated by virtue of differential inclusion and set-valued map theories. By using generalized Bernoulli inequality and Holder inequality, we derived some new sufficient conditions of finite-time stability for the proposed system. Finally two numerical examples are given to show the effectiveness of the proposed approach. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

引用

页码：468 / 485

页数：18

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