• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.37-47
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• 2000

The method of delays is widely used for reconstruction chaotic attractors from experimental observations. Many studies have used a fixed delay time ${\tau}_d$ as the embedding dimension m is increased, but this is not necessarily the best choice for obtaining good convergence of the correlation dimension. Recently, some researchers have suggested that it is better to fix the delay time window ${\tau}_w$ instead. Unfortunately, ${\tau}_w$ cannot be estimated using either the autocorrelation function or the mutual information, and no standard procedure for estimating ${\tau}_w$ has yet emerged. However, a new technique, called the C-C method, can be used to estimate either ${\tau}_d\;or\;{\tau}_w$. Using this method, we show that, for small data sets, fixing ${\tau}_w$, rather than ${\tau}_d$, does indeed lead to a more rapid convergence of the correlation dimension as the embedding dimension m in increased.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.226-229
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• 2008

방위 선택성(orientation selectivity)은 일차 시각 피질에 존재하는 심플 셀(simple cell)의 중요한 특성이다. 이 특성이 어떻게 구현되는가는 아직까지 정확하게 알려지지 않았다. 대표적인 기존 심플 셀의 이론 모델은 시각 자극의 인자마다 대응되는 끌개(attractor)를 가지는 순환 신경망(recurrent neural networks) 모델이 있다. 하지만 자극을 결정하는 인자의 범위는 무한대이므로 끌개 또한 무한대여야 한다는 문제점을 가지고 있다. 본 연구에서는 끌개를 가지지 않는 순환 신경망 모델을 이용하여 심플 셀의 특성을 보임으로서 기존 Recurrent 모델의 문제점을 해결하고 새로운 연구 방향을 제시하고자 한다.

• Journal of KSNVE
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• v.10 no.5
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• pp.849-858
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• 2000

In this paper the chaotic out-of-plane vibrations of the uniformly curved pipe with pulsating flow are theoretically investigated. The derived equations of motion contain the effects of nonlinear curvature and torsional coupling. The corresponding nonlinear ordinary differential equation is a type of nonhomogenous Hill's equation . this is transformed into the averaged equation by averaging theorem. Bifurcation curves of chaotic motion are obtained by Melnikov's method and plotted in several cases of frequency ratios. The theoretically obtained results are demonstrated by numerical simulation. And strange attractors are shown.

• Speech Sciences
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• v.7 no.3
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• pp.167-183
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• 2000

In this paper, we propose two kinds of chaos dimensions, the fuzzy correlation and fuzzy Lyapunov dimensions, for speaker recognition. The proposal is based on the point that chaos enables us to analyze the non-linear information contained in individual's speech signal and to obtain superior discrimination capability. We confirm that the proposed fuzzy chaos dimensions play an important role in enhancing speaker recognition ratio, by absorbing the variations of the reference and test pattern attractors. In order to evaluate the proposed fuzzy chaos dimensions, we suggest speaker recognition using the proposed dimensions. In other words, we investigate the validity of the speaker recognition parameters, by estimating the recognition error according to the discrimination error of an individual speaker from the reference pattern.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.624-626
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• 1997

Canonical Chua's circuit is a simple electronic circuit which exhibits a variety of bifurcation phenomena and attractors. It consists of two capacitors, an inductor, two linear resistors, and a nonlinear resistor. When the circuit exhibits chaotic signals, the nonlinear resistor of canonical Chua's circuit may have three different voltage - current characteristics. In this paper, the design methodology for practical implementation of the nonlinear resistors which have all these characteristics is described. In addition, the effectiveness of result is shown by not only the MATLAB simulation but also the PSPICE simulation.

• Proceedings of the Optical Society of Korea Conference
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• 2004.02a
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• pp.50-51
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• 2004

• Proceedings of the Optical Society of Korea Conference
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• 2004.02a
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• pp.52-53
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• 2004

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.166-169
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• 2000

Chua's circuit is a simple electronic network which exhibits a variety of bifurcati on and attractors. The circuit consists of two capacitors, an inductor, a linear resistor, and a nonlinear resistor. In this paper, a transmitter and a receiver using two identical Chua's circuitsare proposed and a transmission secure communications are investigated. A secure communication method in which the desired information signal is synthesized with the chaos signal created by the Chua's circuit is proposed and information signal is demodulated also using the Chua's circuit. The proposed method is synthesizing the desired information with the chaos circuit by adding the information signal to the chaos signal in the power lime.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2407-2409
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• 2000

Chua's circuit is a simple electronic network which exhibits a variety of bifurcation and attractors. The circuit consists of two capacitors, an inductor, a linear resistor, and a nonlinear resistor. In this paper, a transmitter and a receiver using two identical Chua's circuits are proposed and a equivalent T type wire secure communications are investigated. A secure communication method in which the desired information signal is synthesized with the chaos signal created by the Chua's circuit is proposed and information signal is demodulated also using the Chua's circuit. The proposed method is synthesizing the desired information with the chaos circuit by adding the information signal to the chaos signal in the wire transmission system.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.962-964
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• 1995

In this paper, an integrated chaos analysis system for EEG (ICASE) is designed for the analysis of brain functions based on the chaos theory. Nonlinear dynamic characteristics of EEG such as 3-D attractor, Poincare section, correlation dimension, Lyapunov exponents and power spectrum are extracted by this system. The results show that chaotic attractors which indicate the presence of deterministic, dynamics of complex nature could be identified from a routine EEG recording for normal and pathological activity. This proves that the chaotic analysis of EEG may be an appropriate tool in the classification of brain activity and thus a possible diagnostic tool.