Exponential stability of a class of quaternion‐valued memristor‐based neural network with time‐varying delay via M‐matrix

Author:

Wang Shengye1,Shi Yanchao1ORCID,Guo Jun2

Affiliation:

1. School of Science Southwest Petroleum University Chengdu China

2. College of Applied Mathematics Chengdu University of Information Technology Chengdu China

Abstract

This paper investigates the problems of exponential stability for a class of quaternion‐valued memristor‐based neural networks. By using M‐matrix theory and fixed point theorem, the existence and uniqueness of the equilibrium point of quaternion‐valued neural network are proved, respectively. Then, by combining M‐matrix with exponential stability theory, a non‐factorization method is obtained by using some inequality techniques to give the effective conditions of global exponential stability of quaternion‐valued memristor‐based neural network with time‐varying delay. Finally, numerical examples are given to demonstrate the validity of the derived results.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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