New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type

This research work conducts an investigation of the stability issues of neutral-type Cohen–Grossberg neural network models possessing discrete time delays in states and discrete neutral delays in time derivatives of neuron states. By setting a new generalized appropriate Lyapunov functional candidat...

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Main Author: Ozlem Faydasicok
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/1973548
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author Ozlem Faydasicok
author_facet Ozlem Faydasicok
author_sort Ozlem Faydasicok
collection DOAJ
description This research work conducts an investigation of the stability issues of neutral-type Cohen–Grossberg neural network models possessing discrete time delays in states and discrete neutral delays in time derivatives of neuron states. By setting a new generalized appropriate Lyapunov functional candidate, some novel sufficient conditions are proposed for global asymptotic stability for the considered neural networks of neutral type. This paper exploits some basic properties of matrices in the derivation of the results that establish a set of algebraic mathematical relationships between network parameters of this neural system. A key feature of the obtained stability criteria is to be independent from time and neutral delays. Therefore, the derived results can be easily tested. Moreover, a constructive numerical example is studied to check the verification of presented global stability conditions.
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institution Kabale University
issn 1076-2787
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language English
publishDate 2020-01-01
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spelling doaj-art-16b53eec7aae4215911d892949355e432025-02-03T01:28:32ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/19735481973548New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral TypeOzlem Faydasicok0Department of Mathematics, Faculty of Science Istanbul University, Vezneciler, Istanbul, TurkeyThis research work conducts an investigation of the stability issues of neutral-type Cohen–Grossberg neural network models possessing discrete time delays in states and discrete neutral delays in time derivatives of neuron states. By setting a new generalized appropriate Lyapunov functional candidate, some novel sufficient conditions are proposed for global asymptotic stability for the considered neural networks of neutral type. This paper exploits some basic properties of matrices in the derivation of the results that establish a set of algebraic mathematical relationships between network parameters of this neural system. A key feature of the obtained stability criteria is to be independent from time and neutral delays. Therefore, the derived results can be easily tested. Moreover, a constructive numerical example is studied to check the verification of presented global stability conditions.http://dx.doi.org/10.1155/2020/1973548
spellingShingle Ozlem Faydasicok
New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type
Complexity
title New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type
title_full New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type
title_fullStr New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type
title_full_unstemmed New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type
title_short New Results on Stability of Delayed Cohen–Grossberg Neural Networks of Neutral Type
title_sort new results on stability of delayed cohen grossberg neural networks of neutral type
url http://dx.doi.org/10.1155/2020/1973548
work_keys_str_mv AT ozlemfaydasicok newresultsonstabilityofdelayedcohengrossbergneuralnetworksofneutraltype