DELAY DEPENDENT COMPLEX-VALUED BIDIRECTIONAL WITH STOCHASTIC AND IMPULSIVE EFFECTS: AN EXPONENTIAL STABILITY APPROACH

被引：20

作者：

Maharajan, Chinnamuniyandi ^{[1
]}

Sowmiya, Chandran ^{[2
]}

Xu, Changjin ^{[3
]}

机构：

[1] Kalasalingam Acad Res & Educ, Dept Math, Sch Adv Sci, Krishnankoil 626126, India

[2] Lebanese Amer Univ, Dept Comp Sci & Math, Beirut, Lebanon

[3] Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550025, Peoples R China

来源：

KYBERNETIKA | 2024年 / 60卷 / 03期

关键词：

Complex-valued neural networks; Linear matrix inequality; Lyapunov-Krasovskii functional; BAM neural networks; Exponential stability; Impulsiveeffects; Stochastic noise; discrete delays; distributed delays; leakage delays; mixed time delays; BAM NEURAL-NETWORKS; TIME-VARYING DELAYS; TO-STATE STABILITY; GLOBAL STABILITY; PERIODIC-SOLUTION; LEAKAGE DELAY; CRITERION; DISCRETE; STABILIZATION; EXISTENCE;

D O I：

10.14736/kyb-2024-3-0317

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper investigates the stability in an exponential sense of complex-valued Bidirectional Associative Memory (BAM) neural networks with time delays under the stochastic and impulsive effects. By utilizing the contracting mapping theorem, the existence and uniqueness of the equilibrium point for the proposed complex-valued neural networks are verified. Moreover, based on the Lyapunov - Krasovskii functional construction, matrix inequality techniques and stability theory, some novel time-delayed sufficient conditions are attained in linear matrix inequalities (LMIs) form, which ensure the exponential stability of the trivial solution for the addressed neural networks. Finally, to illustrate the superiority and effects of our theoretical results, two numerical examples with their simulations are provided via MATLAB LMI control toolbox.

引用

页码：317 / 356

页数：40

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