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Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays

In this paper, a class of Cohen-Grossberg fuzzy cellular neural networks (CGFCNNs) with time-varying delays are considered. Initially, the sufficient conditions are proposed to ascertain the existence and uniqueness of the solutions for the considered dynamical system via homeomorphism mapping princ...

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Main Authors: Manikandan, Munia Samy, Ratnavelu, Kurunathan, Balasubramaniam, Pagavathigounder, Ong, Seng Huat
Format: Article
Published: Walter de Gruyter GMBH 2021
Subjects:
QA Mathematics
QC Physics
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
Online Access:http://eprints.um.edu.my/26691/
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spelling my.um.eprints.266912022-04-13T04:14:58Z http://eprints.um.edu.my/26691/ Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays Manikandan, Munia Samy Ratnavelu, Kurunathan Balasubramaniam, Pagavathigounder Ong, Seng Huat QA Mathematics QC Physics TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery In this paper, a class of Cohen-Grossberg fuzzy cellular neural networks (CGFCNNs) with time-varying delays are considered. Initially, the sufficient conditions are proposed to ascertain the existence and uniqueness of the solutions for the considered dynamical system via homeomorphism mapping principle. Then synchronization of the considered delayed neural networks is analyzed by utilizing the drive-response (master-slave) concept, in terms of a linear matrix inequality (LMI), the Lyapunov-Krasovskii (LK) functional, and also using some free weighting matrices. Next, this result is extended so as to establish the robust synchronization of a class of delayed CGFCNNs with polytopic uncertainty. Sufficient conditions are proposed to ascertain that the considered delayed networks are robustly synchronized by using a parameter-dependent LK functional and LMI technique. The restriction on the bounds of derivative of the time delays to be less than one is relaxed. In particular, the concept of fuzzy theory is greatly extended to study the synchronization with polytopic uncertainty which differs from previous efforts in the literature. Finally, numerical examples and simulations are provided to illustrate the effectiveness of the obtained theoretical results. Walter de Gruyter GMBH 2021-02 Article PeerReviewed Manikandan, Munia Samy and Ratnavelu, Kurunathan and Balasubramaniam, Pagavathigounder and Ong, Seng Huat (2021) Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays. International Journal of Nonlinear Sciences and Numerical Simulation, 22 (1). pp. 45-58. ISSN 1565-1339, DOI https://doi.org/10.1515/ijnsns-2019-0256 <https://doi.org/10.1515/ijnsns-2019-0256>. 10.1515/ijnsns-2019-0256
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA Mathematics
QC Physics
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
spellingShingle QA Mathematics
QC Physics
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
Manikandan, Munia Samy
Ratnavelu, Kurunathan
Balasubramaniam, Pagavathigounder
Ong, Seng Huat
Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays
description In this paper, a class of Cohen-Grossberg fuzzy cellular neural networks (CGFCNNs) with time-varying delays are considered. Initially, the sufficient conditions are proposed to ascertain the existence and uniqueness of the solutions for the considered dynamical system via homeomorphism mapping principle. Then synchronization of the considered delayed neural networks is analyzed by utilizing the drive-response (master-slave) concept, in terms of a linear matrix inequality (LMI), the Lyapunov-Krasovskii (LK) functional, and also using some free weighting matrices. Next, this result is extended so as to establish the robust synchronization of a class of delayed CGFCNNs with polytopic uncertainty. Sufficient conditions are proposed to ascertain that the considered delayed networks are robustly synchronized by using a parameter-dependent LK functional and LMI technique. The restriction on the bounds of derivative of the time delays to be less than one is relaxed. In particular, the concept of fuzzy theory is greatly extended to study the synchronization with polytopic uncertainty which differs from previous efforts in the literature. Finally, numerical examples and simulations are provided to illustrate the effectiveness of the obtained theoretical results.
format Article
author Manikandan, Munia Samy
Ratnavelu, Kurunathan
Balasubramaniam, Pagavathigounder
Ong, Seng Huat
author_facet Manikandan, Munia Samy
Ratnavelu, Kurunathan
Balasubramaniam, Pagavathigounder
Ong, Seng Huat
author_sort Manikandan, Munia Samy
title Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays
title_short Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays
title_full Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays
title_fullStr Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays
title_full_unstemmed Synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays
title_sort synchronization of cohen-grossberg fuzzy cellular neural networks with time-varying delays
publisher Walter de Gruyter GMBH
publishDate 2021
url http://eprints.um.edu.my/26691/
_version_ 1735409445620416512
score 13.211869

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