Dissipativity Analysis of Memristor-Based Fractional-Order Hybrid BAM Neural Networks with Time Delays

被引：2

作者：

Liu, Weizhen ^{[1
]}

Jiang, Minghui ^{[1
]}

Fei, Kaifang ^{[1
]}

机构：

[1] China Three Gorges Univ, 8 Daxue Rd, Yichang 443000, Hubei, Peoples R China

来源：

INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION | 2019年 / 20卷 / 7-8期

基金：

中国国家自然科学基金;

关键词：

fractional-order; fractional comparison principle; fractional Halanay inequality; Lyapunov functional; memristor; BAM; GLOBAL EXPONENTIAL STABILITY; EXISTENCE; CALCULUS; FLUID;

D O I：

10.1515/ijnsns-2018-0222

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A new class of memristor-based time-delay fractional-order hybrid BAM neural networks has been put forward. The contraction mapping principle has been adopted to verify the existence and uniqueness of the equilibrium point of the addressed neural networks. By virtue of fractional Halanay inequality and fractional comparison principle, not only the dissipativity has been analyzed, but also a globally attractive set of the new model has been formulated clearly. Numerical simulation is presented to illustrate the feasibility and validity of our theoretical results.

引用

页码：773 / 785

页数：13

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