Dynamic properties of cellular neural networks

Angela Slavova

International Journal of Stochastic Analysis, 1993, vol. 6, 1-10

Abstract:

Dynamic behavior of a new class of information-processing systems called Cellular Neural Networks is investigated. In this paper we introduce a small parameter in the state equation of a cellular neural network and we seek for periodic phenomena. New approach is used for proving stability of a cellular neural network by constructing Lyapunov's majorizing equations. This algorithm is helpful for finding a map from initial continuous state space of a cellular neural network into discrete output. A comparison between cellular neural networks and cellular automata is made.

Date: 1993
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnijsa:287839

DOI: 10.1155/S1048953393000103

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