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http://dx.doi.org/10.5391/JKIIS.2006.16.2.179

Stability Analysis of Limit Cycles on Continuous-time Cyclic Connection Neural Networks  

Park, Cheol-Young (대구대학교 전자공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.16, no.2, 2006 , pp. 179-184 More about this Journal
Abstract
An intuitive understanding of the dynamic pattern generation in asymmetric networks may be considered an essential component in developing models for the dynamic information processing. It has been reported that the neural network with cyclic connections generates multiple limit cycles. The dynamics of discrete time network with cyclic connections has been investigated intensively. However, the dynamics of a cyclic connection neural network in continuous-time has not been well-known due to the considerable complexity involved in its calculation. In this paper, the dynamic behavior of a continuous-time cyclic connection neural network, in which each neuron is connected only to its nearest neurons with binary synaptic weights of ${\pm}1$, has been investigated. Furthermore, the dynamics and stability of the network have been analyzed using a piece-wise linear approximation.
Keywords
continuos-time model; limit cycle; cyclic neural network; stability;
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