Open AccessPeriodic solutions of Cohen-Grossberg-type Bi-directional associative memory neural networks with neutral delays and impulses
Author(s) -
Shuting Chen,
Ke Wang,
Jiang Liu,
Xianke Lin
Publication year - 2020
Publication title -
aims mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 15
ISSN - 2473-6988
DOI - 10.3934/math.2021154
Subject(s) - bidirectional associative memory , artificial neural network , type (biology) , content addressable memory , control theory (sociology) , lyapunov function , class (philosophy) , mathematics , stability (learning theory) , function (biology) , associative property , computer science , topology (electrical circuits) , pure mathematics , control (management) , artificial intelligence , nonlinear system , physics , combinatorics , ecology , quantum mechanics , machine learning , evolutionary biology , biology
This paper considers a class of delayed Cohen-Grossberg-type bi-directonal associative memory neural networks with impulses. By using Mawhin continuation theorem and constructing a new Lyapunov function, some sufficient conditions are presented to guarantee the existence and stability of periodic solutions for the impulsive neural network systems. A simulation example is carried out to illustrate the efficiency of the theoretical results.