Controllability of time-varying cellular neural networks

dc.contributor.authorAziz, Wadie
dc.contributor.authorLara, Teodoro
dc.date.accessioned2021-07-13T17:57:50Z
dc.date.available2021-07-13T17:57:50Z
dc.date.issued2005-11-30
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.description.departmentMathematics
dc.formatText
dc.format.extent10 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationAziz, W., & Lara, T. (2005). Controllability of time-varying cellular neural networks. <i>Electronic Journal of Differential Equations, 2005</i>(135), pp. 1-10.
dc.identifier.issn1072-6691
dc.identifier.urihttps://hdl.handle.net/10877/13860
dc.language.isoen
dc.publisherTexas State University-San Marcos, Department of Mathematics
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceElectronic Journal of Differential Equations, 2005, San Marcos, Texas: Texas State University-San Marcos and University of North Texas.
dc.subjectCellular neural network
dc.subjectCirculant matrix
dc.subjectSun product
dc.titleControllability of time-varying cellular neural networks
dc.typeArticle

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