Cellular Neural Networks with Transient Chaos

Lipo Wang; Wen Liu; Haixiang Shi

doi:10.1109/TCSII.2007.892399

Cellular Neural Networks with Transient Chaos

Lipo Wang, Wen Liu, Haixiang Shi

Research output: Contribution to journal › Article › peer-review

35 Citations (Scopus)

Abstract

A new model of cellular neural networks (CNNs) with transient chaos is proposed by adding negative self-feedbacks into CNNs after transforming the dynamic equation to discrete time via Euler's method. The simulation on the single neuron model shows stable fix points, bifurcation and chaos. Hence, this new CNN model has richer and more flexible dynamics, and therefore may possess better capabilities of solving various problems, compared to the conventional CNN with only stable dynamics.

Original language	English
Pages (from-to)	440-444
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
Volume	54
Issue number	5
DOIs	https://doi.org/10.1109/TCSII.2007.892399
Publication status	Published - 7 May 2007
Externally published	Yes

Keywords

Bifurcation
cellular neural networks (CNNs)
chaos

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10.1109/TCSII.2007.892399

Cite this

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abstract = "A new model of cellular neural networks (CNNs) with transient chaos is proposed by adding negative self-feedbacks into CNNs after transforming the dynamic equation to discrete time via Euler's method. The simulation on the single neuron model shows stable fix points, bifurcation and chaos. Hence, this new CNN model has richer and more flexible dynamics, and therefore may possess better capabilities of solving various problems, compared to the conventional CNN with only stable dynamics.",

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Cellular Neural Networks with Transient Chaos

Abstract

Keywords

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