• Journal of information and communication convergence engineering
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• v.2 no.4
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• pp.237-242
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• 2004

In this paper, we introduce a complex systems synchronization method using hyper-chaos circuit consist of State-Controlled Cellular Neural Network (SC-CNN). We make a complex systems using SC-CNN with the n-double scroll. A complex system is created by applying identical n-double scroll or non-identical n-double scroll and Chua's oscillator with weak coupled method to each cell. Complex systems synchronization were achieved using GS(Generalized Synchronization) method between the transmitter and receiver about each state variable in the SC-CNN.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.701-704
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• 2001

Nowadays there are being done many researches on chaos phenomenon among an assortment of group. Currently, already many applications has been developed, applying this phenomenon to engineering problem. now we are to show how we achieved secure communication through hyperchaotic synchronization system using 1-dimensional CNN(Cellular Neural Network). we focused on materializing secure communication.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.705-708
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• 2001

Nowadays there are being done many researches on chaos phenomenon among many kinds of people. Currently, already many applications has been developed, and they applied this phenomenon to engineering problem. now we have tried to make it possible to use secure communication through hyperchaotic synchronization system using 1-dimensional CNN(Cellular Neural Network). we focused on materializing secure communication.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.223-228
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• 2003

In this paper, we introduce a hyper-chaos secure communication method using hyper-chaos circuit onsist of State-Controlled Cellular Neural Network SC-CNN). We make a hyper-chaos circuit using SC-CNN with the n-double scroll or Chua's oscillator. A hyper-chaos circuit is created by applying identical n-double scroll or non-identical n-double scroll and Chua's oscillator with weak coupled method to each cell. Hyper-chaos ynchronization was achieved using GS (Generalized Synchronization) method between the transmitter and receiver about each state variable in the SC-CNN. In order to secure communication, we have synthesizing the desired information with a hyper-chaos circuit by adding the information signal to the hyper-chaos signal using the SC-CNN in the transmitter. And then, transmitting the synthesized signal to the ideal channel, we confirm secure communication by separating the information signal and the hyper-chaos signal in the receiver.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.575-578
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• 2003

In this paper, we introduce a hyper-chaos secure communication method using Hyper-chaos consist of State-Controlled Cellular Neural Network (SC-CNN). A hyper-chaos circuit is created by applying identical n-double scroll with weak coupled method to each cell. Hyper-chaos synchronization was achieved using embedding synchronization between the transmitter and receiver about in SC CNN. And then, we accomplish secure communication by synthesizing the desired information with a hyper-chaos circuit by embedding the information signal to the only one state variable instead of all state variables in the driven-synchronization method. After transmitting the synthesized signal to the identical channel, we confirm secure communication by separating the information signal and the hyper-chaos signal in the receiver.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.266-269
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• 2001

이미지와 비디오신호 처리는 영상인식에 있어 중요한 요소이다. 셀룰라 신경회로망은 영상과 관련된 분야에서 많이 사용되고 있다. 그 응용분야로서 본 논문에서는 로봇축구에 적용하기 위하여 8색의 컬러구분을 통한 축구로봇의 인식과, 또한 경기장의 격자구조의 분할을 통한 셀간의 이동을 통하여 간단한 경로 이동과 급변하는 환경의 변화에 적응하는 시스템을 구현한다. CNN을 이용한 영상처리에서는 각 셀을 화면상의 각 화소에 대응하고, 셀의 출력의 값을 화소의 값으로 정한다. CNN을 이용한 경로계획에서는 각 셀이 격자구조 경기장의 한 부분이 되고, 정의된 출력의 셀이 로봇이 이동할 목표가 된다.