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

Hien,LV, Loan,TT, Huyen Trang,BT and Trinh,H 2014, Existence and global asymptotic stability of positive periodic solution of delayed Cohen-Grossberg neural networks, Applied Mathematics and Computation, vol. 240, pp. 200-212, doi: 10.1016/j.amc.2014.04.078.

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Title Existence and global asymptotic stability of positive periodic solution of delayed Cohen-Grossberg neural networks
Author(s) Hien,LV
Loan,TT
Huyen Trang,BT
Trinh,HORCID iD for Trinh,H orcid.org/0000-0003-3438-9969
Journal name Applied Mathematics and Computation
Volume number 240
Start page 200
End page 212
Total pages 13
Publisher Elsevier Inc
Place of publication Philadelphia, United States
Publication date 2014-08-01
ISSN 0096-3003
Keyword(s) 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
Summary 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.
Language eng
DOI 10.1016/j.amc.2014.04.078
Field of Research 010203 Calculus of Variations, Systems Theory and Control Theory
010204 Dynamical Systems in Applications
090602 Control Systems, Robotics and Automation
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Grant ID DP130101532
Copyright notice ©2014, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30068302

Document type: Journal Article
Collection: School of Engineering
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