Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays

This article is concerned with the global [Formula: see text] stabilization for a class of fractional-order memristive neural networks with time delays (FMDNNs). Two kinds of control scheme (i.e., state feedback control law and output feedback control law) are employed to stabilize a class of FMDNNs...

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Detalles Bibliográficos
Autores principales: Liu, Ling, Wu, Ailong, Song, Xingguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4938841/
https://www.ncbi.nlm.nih.gov/pubmed/27462482
http://dx.doi.org/10.1186/s40064-016-2374-3
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author Liu, Ling
Wu, Ailong
Song, Xingguo
author_facet Liu, Ling
Wu, Ailong
Song, Xingguo
author_sort Liu, Ling
collection PubMed
description This article is concerned with the global [Formula: see text] stabilization for a class of fractional-order memristive neural networks with time delays (FMDNNs). Two kinds of control scheme (i.e., state feedback control law and output feedback control law) are employed to stabilize a class of FMDNNs. Several stabilization conditions in form of algebraic criteria are presented based on a new fractional-order Lyapunov function method and Leibniz rule. Some examples are given to substantiate the effectiveness of the presented theoretical results.
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spelling pubmed-49388412016-07-26 Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays Liu, Ling Wu, Ailong Song, Xingguo Springerplus Research This article is concerned with the global [Formula: see text] stabilization for a class of fractional-order memristive neural networks with time delays (FMDNNs). Two kinds of control scheme (i.e., state feedback control law and output feedback control law) are employed to stabilize a class of FMDNNs. Several stabilization conditions in form of algebraic criteria are presented based on a new fractional-order Lyapunov function method and Leibniz rule. Some examples are given to substantiate the effectiveness of the presented theoretical results. Springer International Publishing 2016-07-09 /pmc/articles/PMC4938841/ /pubmed/27462482 http://dx.doi.org/10.1186/s40064-016-2374-3 Text en © The Author(s) 2016 Open AccessThis 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
Liu, Ling
Wu, Ailong
Song, Xingguo
Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays
title Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays
title_full Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays
title_fullStr Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays
title_full_unstemmed Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays
title_short Global [Formula: see text] stabilization of fractional-order memristive neural networks with time delays
title_sort global [formula: see text] stabilization of fractional-order memristive neural networks with time delays
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4938841/
https://www.ncbi.nlm.nih.gov/pubmed/27462482
http://dx.doi.org/10.1186/s40064-016-2374-3
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AT wuailong globalformulaseetextstabilizationoffractionalordermemristiveneuralnetworkswithtimedelays
AT songxingguo globalformulaseetextstabilizationoffractionalordermemristiveneuralnetworkswithtimedelays

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