Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks

In this paper, a new class of impulsive neural networks with fractional-like derivatives is defined, and the practical stability properties of the solutions are investigated. The stability analysis exploits a new type of Lyapunov-like functions and their derivatives. Furthermore, the obtained result...

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Autores principales: Stamov, Gani, Stamova, Ivanka, Martynyuk, Anatoliy, Stamov, Trayan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516808/
https://www.ncbi.nlm.nih.gov/pubmed/33286111
http://dx.doi.org/10.3390/e22030337
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author Stamov, Gani
Stamova, Ivanka
Martynyuk, Anatoliy
Stamov, Trayan
author_facet Stamov, Gani
Stamova, Ivanka
Martynyuk, Anatoliy
Stamov, Trayan
author_sort Stamov, Gani
collection PubMed
description In this paper, a new class of impulsive neural networks with fractional-like derivatives is defined, and the practical stability properties of the solutions are investigated. The stability analysis exploits a new type of Lyapunov-like functions and their derivatives. Furthermore, the obtained results are applied to a bidirectional associative memory (BAM) neural network model with fractional-like derivatives. Some new results for the introduced neural network models with uncertain values of the parameters are also obtained.
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spelling pubmed-75168082020-11-09 Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks Stamov, Gani Stamova, Ivanka Martynyuk, Anatoliy Stamov, Trayan Entropy (Basel) Article In this paper, a new class of impulsive neural networks with fractional-like derivatives is defined, and the practical stability properties of the solutions are investigated. The stability analysis exploits a new type of Lyapunov-like functions and their derivatives. Furthermore, the obtained results are applied to a bidirectional associative memory (BAM) neural network model with fractional-like derivatives. Some new results for the introduced neural network models with uncertain values of the parameters are also obtained. MDPI 2020-03-15 /pmc/articles/PMC7516808/ /pubmed/33286111 http://dx.doi.org/10.3390/e22030337 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Stamov, Gani
Stamova, Ivanka
Martynyuk, Anatoliy
Stamov, Trayan
Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks
title Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks
title_full Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks
title_fullStr Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks
title_full_unstemmed Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks
title_short Design and Practical Stability of a New Class of Impulsive Fractional-Like Neural Networks
title_sort design and practical stability of a new class of impulsive fractional-like neural networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516808/
https://www.ncbi.nlm.nih.gov/pubmed/33286111
http://dx.doi.org/10.3390/e22030337
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