pth moment exponential stability of memristor Cohen-Grossberg BAM neural networks with time-varying delays and reaction-diffusion

被引：15

作者：

Priya, Bandana ^{[1
]}

Ali, M. Syed ^{[2
]}

Thakur, Ganesh Kumar ^{[3
]}

Sanober, Sumaya ^{[4
]}

Dhupia, Bhawna ^{[4
]}

机构：

[1] GL Bajaj Inst Technol & Management, Dept Appl Sci, Greater Noida, India

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

[3] Krishna Engn Coll, Dept Appl Sci, Ghaziabad, Uttar Pradesh, India

[4] Prince Sattam Bin Abdulaziz Univ, Coll Arts & Sci, Dept Comp Sci, Wadi Aldawaser 11991, Saudi Arabia

来源：

CHINESE JOURNAL OF PHYSICS | 2021年 / 74卷

关键词：

Stochastic memristor CGBAMNNs; Time-varying delays; Reaction-diffusion; NEUTRAL-TYPE; DISCRETE; SYNCHRONIZATION; EXISTENCE;

D O I：

10.1016/j.cjph.2021.06.027

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

A B S T R A C T In this paper, stability for a class of stochastic memristor Cohen-Grossberg BAM neural networks with time-varying delays and reaction-diffusion are considered. A set of novel sufficient conditions on pth moment exponential stability of the equilibrium point are investigated for the considered system. We constructed Lyapunov functional and utilized stochastic stability theory and Itos differential formula. Finally, two examples are provided to illustrate the effectiveness of the derived main results.

引用

页码：184 / 194

页数：11

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