Stability analysis for periodic solutions of fuzzy shunting inhibitory CNNs with delays

dc.contributor.authorArdak Kashkynbayev
dc.contributor.authorJinde Cao
dc.contributor.authorZhaksybek Damiyev
dc.date.accessioned2025-08-13T06:05:48Z
dc.date.available2025-08-13T06:05:48Z
dc.date.issued2019
dc.description.abstractWe consider fuzzy shunting inhibitory cellular neural networks (FSICNNs) with time-varying coefficients and constant delays. By virtue of continuation theorem of coincidence degree theory and Cauchy–Schwartz inequality, we prove the existence of periodic solutions for FSICNNs. Furthermore, by employing a suitable Lyapunov functional we establish sufficient criteria which ensure global exponential stability of the periodic solutions. Numerical simulations that support the theoretical discussions are depicted.
dc.identifier.citationKashkynbayev, A.; Cao, J.; Damiyev, Z. (2019). Stability analysis for periodic solutions of fuzzy shunting inhibitory CNNs with delays. Advances in Difference Equations, 2019, Article 384. DOI: 10.1186/s13662-019-2321-z
dc.identifier.urihttps://nur.nu.edu.kz/handle/123456789/9195
dc.language.isoen
dc.publisherAdvances in Difference Equations (SpringerOpen)
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/
dc.subjectfuzzy shunting inhibitory cellular neural networks
dc.subjectdelay differential equations
dc.subjectperiodic solutions
dc.subjectglobal exponential stability
dc.subjectLyapunov functional
dc.subjecttype of access: open access
dc.titleStability analysis for periodic solutions of fuzzy shunting inhibitory CNNs with delays
dc.typeArticle

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