Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays

In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete...

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Detalles Bibliográficos
Autores principales: Zhang, Hao, Wang, Xing-yuan, Lin, Xiao-hui, Liu, Chong-xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3979734/
https://www.ncbi.nlm.nih.gov/pubmed/24714386
http://dx.doi.org/10.1371/journal.pone.0093838
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author Zhang, Hao
Wang, Xing-yuan
Lin, Xiao-hui
Liu, Chong-xin
author_facet Zhang, Hao
Wang, Xing-yuan
Lin, Xiao-hui
Liu, Chong-xin
author_sort Zhang, Hao
collection PubMed
description In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete-time model of complex-valued neural networks is derived. Moreover, by using the complex-valued Lyapunov-Krasovskii functional method and linear matrix inequality as tools, sufficient conditions of the synchronization stability are obtained. In numerical simulation, examples are presented to show the effectiveness of our method.
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spelling pubmed-39797342014-04-11 Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays Zhang, Hao Wang, Xing-yuan Lin, Xiao-hui Liu, Chong-xin PLoS One Research Article In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete-time model of complex-valued neural networks is derived. Moreover, by using the complex-valued Lyapunov-Krasovskii functional method and linear matrix inequality as tools, sufficient conditions of the synchronization stability are obtained. In numerical simulation, examples are presented to show the effectiveness of our method. Public Library of Science 2014-04-08 /pmc/articles/PMC3979734/ /pubmed/24714386 http://dx.doi.org/10.1371/journal.pone.0093838 Text en © 2014 Zhang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zhang, Hao
Wang, Xing-yuan
Lin, Xiao-hui
Liu, Chong-xin
Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays
title Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays
title_full Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays
title_fullStr Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays
title_full_unstemmed Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays
title_short Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays
title_sort stability and synchronization for discrete-time complex-valued neural networks with time-varying delays
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3979734/
https://www.ncbi.nlm.nih.gov/pubmed/24714386
http://dx.doi.org/10.1371/journal.pone.0093838
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AT wangxingyuan stabilityandsynchronizationfordiscretetimecomplexvaluedneuralnetworkswithtimevaryingdelays
AT linxiaohui stabilityandsynchronizationfordiscretetimecomplexvaluedneuralnetworkswithtimevaryingdelays
AT liuchongxin stabilityandsynchronizationfordiscretetimecomplexvaluedneuralnetworkswithtimevaryingdelays

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