Bifurcation and Chaos in Cellular Neural Networks

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Abstract

In this study bifurcation phenomena and chaotic behavior in cellular neural networks are investigated. In a two-cell autonomous system, Hopf-like bifurcation has been found, at which the flow around the origin, an equilibrium point of the system, changes from asymptotically stable to periodic. As the parameter grows further, by reaching another bifurcation value, the generated limit cycle disappears and the network becomes convergent again. Chaos is also presented in a three-cell autonomous system. It is shown that the chaotic attractor found here has properties similar to the famous double scroll attractor.

Original languageEnglish
Pages (from-to)166-173
Number of pages8
JournalIEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume40
Issue number3
DOIs
StatePublished - Mar 1993

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