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dc.contributor.authorAziz, Wadie ( Orcid Icon 0000-0002-6725-5871 )
dc.contributor.authorLara, Teodoro ( )
dc.date.accessioned2021-07-13T17:57:50Z
dc.date.available2021-07-13T17:57:50Z
dc.date.issued2005-11-30
dc.identifier.citationAziz, W., & Lara, T. (2005). Controllability of time-varying cellular neural networks. Electronic Journal of Differential Equations, 2005(135), pp. 1-10.en_US
dc.identifier.issn1072-6691
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/13860
dc.description.abstractIn this work, we consider the model of Cellular Neural Network (CNN) introduced by Chua and Yang in 1988, but with the cloning templates ω-periodic in time. By imposing periodic boundary conditions the matrices involved in the system become circulant and ω-periodic. We show some results on the controllability of the linear model using a Theorem by Brunovsky for the case of linear and ω-periodic system. Also we use this approach in image detection, specifically foreground, background and contours of figures in different scales of grey.
dc.formatText
dc.format.extent10 pages
dc.format.medium1 file (.pdf)
dc.language.isoenen_US
dc.publisherTexas State University-San Marcos, Department of Mathematicsen_US
dc.sourceElectronic Journal of Differential Equations, 2005, San Marcos, Texas: Texas State University-San Marcos and University of North Texas.
dc.subjectCellular neural networken_US
dc.subjectCirculant matrixen_US
dc.subjectSun producten_US
dc.titleControllability of time-varying cellular neural networksen_US
dc.typepublishedVersion
txstate.documenttypeArticle
dc.rights.licenseCreative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.description.departmentMathematics


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