文献类型：期刊文献

英文题名：Exponential Stability of Stochastic Inertial Cohen-Grossberg Neural Networks

作者：Zhang, Yuehong[1];Li, Zhiying[1];Jiang, Wangdong[1];Liu, Wei[1]

机构：[1]Shaoxing Univ, Yuanpei Coll, Fundamental Dept, Qunxian Middle Rd 2799, Shaoxing City, Zhejiang, Peoples R China

年份：2023

卷号：37

期号：01

外文期刊名：INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE

收录：SCI-EXPANDED(收录号：WOS:000924161400001)、、EI(收录号：20230613563597)、Scopus(收录号：2-s2.0-85147513786)、WOS

基金：This work greatly acknowledges the support offered by the Science Project of Zhejiang Educational Department (No. Y202145903), the Science Project of Shaoxing University (No. 2020LG1009) and the Science Project of Shaoxing University Yuanpei College (No. KY2020C01, KY2021C04).

语种：英文

外文关键词：Stochastic inertial; Cohen-Grossberg neural networks; basic solution matrix; MSES; PMES

外文摘要：In this paper, we adopt two methods to study the problem. Initially, directly from the second-order differential equation, we obtain a sufficient condition (SC) for the mean square exponential stability (MSES) of the system at the equilibrium point by constructing a suitable function and applying some properties of calculus. Thereafter, the system is transformed into a vector form, using the basic solution matrix of linear differential equation, constructing a piecewise function and using the generalized Halanay one-dimensional delay differential inequality, another SC is given for the P-moment exponential stability (PMES) of the system at the equilibrium point. Finally, two examples are used to investigate the correctness and demonstrate that each SC has own advantage, the suitable theorem can be selected according to the parameters.