Existence and global asymptotic stability of positive periodic solution of delayed Cohen-Grossberg neural networks


Autoria(s): Hien,LV; Loan,TT; Huyen Trang,BT; Trinh,H
Data(s)

01/08/2014

Resumo

In this paper, a class of periodic Cohen-Grossberg neural networks with discrete and distributed time-varying delays is considered. By an extension of the Lyapunov-Krasovskii functional method, a novel criterion for the existence and uniqueness and global asymptotic stability of positive periodic solution is derived in terms of M-matrix without any restriction on uniform positiveness of the amplification functions. Comparison and illustrative examples are given to illustrate the effectiveness of the obtained results. © 2014 Elsevier Inc. All rights reserved.

Identificador

http://hdl.handle.net/10536/DRO/DU:30068302

Idioma(s)

eng

Publicador

Elsevier Inc

Relação

DP130101532

http://dro.deakin.edu.au/eserv/DU:30068302/hien-existenceandglobal-2014.pdf

http://www.dx.doi.org/10.1016/j.amc.2014.04.078

Direitos

2014, Elsevier

Palavras-Chave #Cohen-Grossberg neural networks #M-matrix #Non-autonomous systems #Periodic solutions #Time-varying delays #Science & Technology #Physical Sciences #Mathematics, Applied #Mathematics #DISTRIBUTED DELAYS #EXPONENTIAL STABILITY #DISCRETE #CRITERIA #DESIGN #DYNAMICS #LEAKAGE
Tipo

Journal Article