In this paper, after the introduction of the definition of State Controlled Cellular Neural Networks (SC-CNNs), it is shown that they are able to generate complex dynamics of circuits showing strange behaviour. Theoretical propositions are presented to fix the templates of the SC-CNNs in such a way as to exactly match the dynamic behaviour of the circuits considered. The easy and cheap implementation of the proposed SC-CNN devices is illustrated and a gallery of experimentally obtained strange attractors are shown to confirm the practical suitability of the outlined strategy.

In this paper, after the introduction of the definition of State Controlled Cellular Neural Networks (SC-CNNs), it is shown that they are able to generate complex dynamics of circuits showing strange behaviour. Theoretical propoitions are presented to fix the templates of the SC-CNNs in such a way as to exactly match the dynamic behaviour of the circuits considered. The easy and cheap implementation of the proposed SC-CNN devices is illustrated and a gallery of experimentally obtained strange attractors are shown to confirm the practical suitability of the outlined strategy.

State controlled CNN: A new strategy for generating high complex dynamics

ARENA, Paolo Pietro;BAGLIO, Salvatore;FORTUNA, Luigi;
1996-01-01

Abstract

In this paper, after the introduction of the definition of State Controlled Cellular Neural Networks (SC-CNNs), it is shown that they are able to generate complex dynamics of circuits showing strange behaviour. Theoretical propoitions are presented to fix the templates of the SC-CNNs in such a way as to exactly match the dynamic behaviour of the circuits considered. The easy and cheap implementation of the proposed SC-CNN devices is illustrated and a gallery of experimentally obtained strange attractors are shown to confirm the practical suitability of the outlined strategy.
1996
In this paper, after the introduction of the definition of State Controlled Cellular Neural Networks (SC-CNNs), it is shown that they are able to generate complex dynamics of circuits showing strange behaviour. Theoretical propositions are presented to fix the templates of the SC-CNNs in such a way as to exactly match the dynamic behaviour of the circuits considered. The easy and cheap implementation of the proposed SC-CNN devices is illustrated and a gallery of experimentally obtained strange attractors are shown to confirm the practical suitability of the outlined strategy.
cellular neural networks; non linear circuits; chaos
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/12546
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