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Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties

The present study considers the robust stability for impulsive complex-valued neural networks (CVNNs) with discrete time delays. By applying the homeomorphic mapping theorem and some inequalities in a complex domain, some sufficient conditions are obtained to prove the existence and uniqueness of th...

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Detalles Bibliográficos
Autores principales: Tan, Yuanshun, Tang, Sanyi, Yang, Jin, Liu, Zijian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5594064/
https://www.ncbi.nlm.nih.gov/pubmed/28959116
http://dx.doi.org/10.1186/s13660-017-1490-0
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author Tan, Yuanshun
Tang, Sanyi
Yang, Jin
Liu, Zijian
author_facet Tan, Yuanshun
Tang, Sanyi
Yang, Jin
Liu, Zijian
author_sort Tan, Yuanshun
collection PubMed
description The present study considers the robust stability for impulsive complex-valued neural networks (CVNNs) with discrete time delays. By applying the homeomorphic mapping theorem and some inequalities in a complex domain, some sufficient conditions are obtained to prove the existence and uniqueness of the equilibrium for the CVNNs. By constructing appropriate Lyapunov-Krasovskii functionals and employing the complex-valued matrix inequality skills, the study finds the conditions to guarantee its global robust stability. A numerical simulation illustrates the correctness of the proposed theoretical results.
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spelling pubmed-55940642017-09-26 Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties Tan, Yuanshun Tang, Sanyi Yang, Jin Liu, Zijian J Inequal Appl Research The present study considers the robust stability for impulsive complex-valued neural networks (CVNNs) with discrete time delays. By applying the homeomorphic mapping theorem and some inequalities in a complex domain, some sufficient conditions are obtained to prove the existence and uniqueness of the equilibrium for the CVNNs. By constructing appropriate Lyapunov-Krasovskii functionals and employing the complex-valued matrix inequality skills, the study finds the conditions to guarantee its global robust stability. A numerical simulation illustrates the correctness of the proposed theoretical results. Springer International Publishing 2017-09-11 2017 /pmc/articles/PMC5594064/ /pubmed/28959116 http://dx.doi.org/10.1186/s13660-017-1490-0 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Tan, Yuanshun
Tang, Sanyi
Yang, Jin
Liu, Zijian
Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties
title Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties
title_full Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties
title_fullStr Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties
title_full_unstemmed Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties
title_short Robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties
title_sort robust stability analysis of impulsive complex-valued neural networks with time delays and parameter uncertainties
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5594064/
https://www.ncbi.nlm.nih.gov/pubmed/28959116
http://dx.doi.org/10.1186/s13660-017-1490-0
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