Existence of periodic solutions for the discrete-time counterpart of a neutral-type cellular neural network with time-varying delays and impulses

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dc.contributor.authorAl-Zahrani, Eadah
dc.contributor.authorCovachev, Valéry
dc.contributor.authorAkca, Haydar
dc.contributor.authorETAL..
dc.date.accessioned2021-12-29T10:27:51Z
dc.date.accessioned2023-08-19T09:16:09Z
dc.date.available2021-12-29T10:27:51Z
dc.date.available2023-08-19T09:16:09Z
dc.date.issued2017-07
dc.descriptionAkça, H., Al-Zahrani, E., Covachev, V., & Covacheva, Z. (2017, July). Existence of periodic solutions for the discrete-time counterpart of a neutral-type cellular neural network with time-varying delays and impulses. In AIP Conference Proceedings (Vol. 1863, No. 1, p. 140002). AIP Publishing LLC.en_US
dc.description.abstractFrom the mathematical point of view, a cellular neural network (CNN) can be characterized by an array of identical nonlinear dynamical systems called cells (neurons) that are locally interconnected. Using the semi-discretization method, in the present talk we construct a discrete-time counterpart of a neutral-type CNN with time-varying delays and impulses. Sufficient conditions for the existence of periodic solutions of the discrete-time system thus obtained are found by using the continuation theorem of coincidence degree theory.en_US
dc.identifier.citationAkça, H., Al-Zahrani, E., Covachev, V., & Covacheva, Z. (2017, July). Existence of periodic solutions for the discrete-time counterpart of a neutral-type cellular neural network with time-varying delays and impulses. In AIP Conference Proceedings (Vol. 1863, No. 1, p. 140002). AIP Publishing LLC.
dc.identifier.doihttps://doi.org/10.1063/1.4992309
dc.identifier.urihttps://edms.wexl.in/handle/1/2068
dc.language.isoenen_US
dc.publisherAIPen_US
dc.subjectExistence of periodic solutionsen_US
dc.subjectDiscrete-time counterparten_US
dc.subjectNeutral-type cellularen_US
dc.subjectDelays and impulsesen_US
dc.titleExistence of periodic solutions for the discrete-time counterpart of a neutral-type cellular neural network with time-varying delays and impulsesen_US
dc.title.alternativeAIP Conference Proceedings > Volume 1863, Issue 1 > 10.1063/1.4992309en_US
dc.typeArticleen_US

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Over the past two decades neural networks have been widely studied since they have been successfully applied to various processing problems such as optimization, image processing, associative memory and many other fields (see [4] and references given therein). Different types of applications depend on the dynamical behaviours of the neural networks. Cellular neural networks (CNNs) were introduced in the 1980s by Chua and Yang
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