Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Analysis of Dynamical State Transition and Effects of Chaotic Signal in Continuous-Time Cyclic Neural Network

리미트사이클을 발생하는 연속시간 모델 순환결합형 신경회로망에서 카오스 신호의 영향

  • Published : 2006.08.01
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Abstract

It is well-known that a neural network with cyclic connections generates plural limit cycles, thus, being used as a memory system for storing large number of dynamic information. In this paper, a continuous-time cyclic connection neural network was built so that each neuron is connected only to its nearest neurons with binary synaptic weights of ${\pm}1$. The type and the number of limit cycles generated by such network has also been demonstrated through simulation. In particular, the effect of chaos signal for transition between limit cycles has been tested. Furthermore, it is evaluated whether the chaotic noise is more effective than random noise in the process of the dynamical neural networks.

순환결합형 신경회로망은 복수 개의 리미트사이클을 생성하며 따라서, 많은 동적 정보를 저장할 수 있는 메모리 시스템으로 사용할 수 있다는 것이 알려져 있다. 본 논문에서는 각 뉴런이 최근접 뉴런에만 이진화한 결합하중 ${\pm}1$로 연결된 연속 시간모델 순환결합형 신경회로망을 구현하였다. 그리고 이런 회로망을 통해 생성되는 리미트사이클의 수와 패턴을 시뮬레이션을 통하여 나타내었다. 또한 카오스 신호를 인가하여 리미트사이클 사이의 천이 가능성을 입증하였다. 특히, 카오스 신호 이외의 랜덤 노이즈를 이용한 해석을 통하여 동적 신경회로망에 카오스 노이즈를 인가하는 경우의 유효성을 검토하였다.

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References

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