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Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions

This paper concerns the problem of enhanced results on robust finite time passivity for uncertain discrete time Markovian jumping BAM delayed neural networks with leakage delay. By implementing a proper Lyapunov–Krasovskii functional candidate, reciprocally convex combination method, and linear matr...

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Detalles Bibliográficos
Autores principales: Maharajan, C., Raja, R., Cao, Jinde, Ravi, G., Rajchakit, G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5942391/
https://www.ncbi.nlm.nih.gov/pubmed/29770144
http://dx.doi.org/10.1186/s13662-018-1553-7
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author Maharajan, C.
Raja, R.
Cao, Jinde
Ravi, G.
Rajchakit, G.
author_facet Maharajan, C.
Raja, R.
Cao, Jinde
Ravi, G.
Rajchakit, G.
author_sort Maharajan, C.
collection PubMed
description This paper concerns the problem of enhanced results on robust finite time passivity for uncertain discrete time Markovian jumping BAM delayed neural networks with leakage delay. By implementing a proper Lyapunov–Krasovskii functional candidate, reciprocally convex combination method, and linear matrix inequality technique, we derive several sufficient conditions for varying the passivity of discrete time BAM neural networks. Further, some sufficient conditions for finite time boundedness and passivity for uncertainties are proposed by employing zero inequalities. Finally, the enhancement of the feasible region of the proposed criteria is shown via numerical examples with simulation to illustrate the applicability and usefulness of the proposed method.
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spelling pubmed-59423912018-05-14 Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions Maharajan, C. Raja, R. Cao, Jinde Ravi, G. Rajchakit, G. Adv Differ Equ Research This paper concerns the problem of enhanced results on robust finite time passivity for uncertain discrete time Markovian jumping BAM delayed neural networks with leakage delay. By implementing a proper Lyapunov–Krasovskii functional candidate, reciprocally convex combination method, and linear matrix inequality technique, we derive several sufficient conditions for varying the passivity of discrete time BAM neural networks. Further, some sufficient conditions for finite time boundedness and passivity for uncertainties are proposed by employing zero inequalities. Finally, the enhancement of the feasible region of the proposed criteria is shown via numerical examples with simulation to illustrate the applicability and usefulness of the proposed method. Springer International Publishing 2018-03-27 2018 /pmc/articles/PMC5942391/ /pubmed/29770144 http://dx.doi.org/10.1186/s13662-018-1553-7 Text en © The Author(s) 2018 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
Maharajan, C.
Raja, R.
Cao, Jinde
Ravi, G.
Rajchakit, G.
Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions
title Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions
title_full Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions
title_fullStr Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions
title_full_unstemmed Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions
title_short Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions
title_sort global exponential stability of markovian jumping stochastic impulsive uncertain bam neural networks with leakage, mixed time delays, and α-inverse hölder activation functions
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5942391/
https://www.ncbi.nlm.nih.gov/pubmed/29770144
http://dx.doi.org/10.1186/s13662-018-1553-7
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