Convergence behaviour of solutions to delay cellular neural networks with non-periodic coefficients

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dc.contributor.authorXiao, Bing
dc.contributor.authorZhang, Hong
dc.date.accessioned2021-08-05T16:01:15Z
dc.date.available2021-08-05T16:01:15Z
dc.date.issued2007-03-15
dc.description.abstractIn this note we studied delay neural networks without periodic coefficients. Sufficient conditions are established to ensure that all solutions of the networks converge to a periodic function. An example is given to illustrate our results.
dc.description.departmentMathematics
dc.formatText
dc.format.extent7 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationXiao, B., & Zhang, H. (2007). Convergence behaviour of solutions to delay cellular neural networks with non-periodic coefficients. <i>Electronic Journal of Differential Equations, 2007</i>(46), pp. 1-7.
dc.identifier.issn1072-6691
dc.identifier.urihttps://hdl.handle.net/10877/14207
dc.language.isoen
dc.publisherTexas State University-San Marcos, Department of Mathematics
dc.rightsAttribution 4.0 International
dc.rights.holderThis work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceElectronic Journal of Differential Equations, 2007, San Marcos, Texas: Texas State University-San Marcos and University of North Texas.
dc.subjectCellular neural networks
dc.subjectConvergence
dc.subjectDelays
dc.titleConvergence behaviour of solutions to delay cellular neural networks with non-periodic coefficients
dc.typeArticle

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