• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.11 s.242
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• pp.1248-1256
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• 2005

This study was undertaken to investigate the flow characteristics of emulsified fuel with the ultrasonic energy-adding system by using the chaotic method. Efffcts of water contents within emulsified fuel, flow rate and tube length with 5m in diameter from an emulsified chamber has been discussed on the strange attractor and power spectral density function. Five probe sensors were set up from 0.5 to 2.5m by length in 0.5m increments in the tube. In particular, the chaotic features of this system have been practically characterized in terms of chaotic statistics such as the power spectral density function and phase space portraits by resorting to the somewhat noble deterministic chaos theory. In the tube, the dominant frequency increased with increasing water contents and flow rate, but decreased a little with an increase in the length from the emulsified chamber.

• The Korean Journal of Financial Management
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• v.11 no.1
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• pp.73-96
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• 1994

본 연구는 비선형적 제반 특성을 종합적으로 반영하는 chaos모형을 우리나라의 종합 주가지수 수익률의 시계열 자료에 적용하여 주식 수익률의 비선형적 행태를 실증적으로 분석하였다. 실증분석의 결과, 종합 주가지수 수익률은 내재차원이 14이고, 상관차원이 5에서 6사이인 chaos적 특성을 갖고 있다는 것을 알 수 있었다. 또한 상관차원이 5에서 6사이라는 것은 우리나라 주식시장에 영향을 미치는 주요 변수가 약 6개라는 것을 의미한다. 특히 리야푸노프 지수에 의한 분석 결과는 주별 및 일별 수익률에서 이들 값이 공히 양의 값에 수렴하고 있어 우리나라 주식 수익률은 이상한 끌개(strange attractor)를 갖는chaos적 행태를 보인다고 결론 지울 수 있다. 콜모고로프 엔트로피에 의한 분석 결과는 주별 수익률 및 일별 수익률의 경우에 모두 $0.25{\pm}0.05$의 유한한 값으로 나타나고 있으며, 또한 이들 일별 및 주별양 수익률이 유사한 값을 보이고 있어 서로 유사한 chaos적 특성을 갖고 있다는 것을 알게되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.2
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• pp.365-370
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• 2001

In this paper, we analyze behavior of complemented CA derived from a linear Two-Predecessor MACA(TPMACA) and obtain the state-transition diagram of complemented CA by using a basic path in the 0-Dee of a linear TPMACA.

• 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.

• Journal of the Korean Society for Railway
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• v.5 no.2
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• pp.55-60
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• 2002

This study proposes the post-processor simulator construction of ultrasonic signal for integrity evaluation of railway truck. For these purposes, the ultrasonic signals for defects(crack) of weld zone in frames are acquired in the type of time series data and echo strength. The detection of the natural defects in railway truck is performed using the characteristics of echodynamic pattern in ultrasonic signal. The constructed post-processor simulator agree fairly well with the measured results of test block(defect location, beam propagation distance, echo strength, etc). Proposed post-processor simulator construction of ultrasonic in this study can be used for the integrity evaluation of railway truck.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.1
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• pp.22-27
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• 2001

본 논문에서는 복잡한 하이퍼카오스 신호를 발생시키는 HVPM (Hyperchaotic Volume Preserving Maps) 모델의 회로를 제안하고, 보드상에서 구현하고자 한다. 제안한 HVPM 모델은 3차원 이산시간(discrete-time) 연립차분방정식으로 구성되어 있으며, 비선형 사상(maps)과 모듈러(modulus) 함수를 사용하여 랜덤한 카오스 어트랙터(attractor)를 발생시킨다. 이러한 HVPM 모델을 하드웨로 구현하기 위하여 연산 부분은 연산증폭기를 사용하고, 매핑(mapping) 부분은 N형 함수와 비교기를 사용하여 설계한다. 특히, N형의 비선형 함수는 CMOS 전달특성과 선형증폭기의 출력특성을 조합하여 독특하게 구현하였다. 구현한 보드상의 실험에서 카오스 시스템 파라미터 값에 대응하는 가변저항기를 조절하여 비주기적인 하이퍼카오스 신호를 발생시킴을 입증하였다. 또한 출력된 카오스 신호들간의 오실로스코프 사진에서 위상공간(phase space)의 동적응답은 랜덤한 어트랙터를 발생시킴을 확인할 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.545-549
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• 1999

Previous studies on high impedance faults assumed that the erratic behavior of fault current would be random. In this paper we prove that the nature of the high impedance faults is indeed a deterministic chaos not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents in order to evaluate the orbital instability peculiar to deterministic chaos dynamically and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. In addition qualitative analysis such a s phase planes Poincare maps obtained from fault currents indicate that the irregular behavior is described by strange attractor.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.297-299
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• 2003

This paper proposes a totally new method in the chaos characteristics analysis of power systems, the introduction of topological invariants. Using a return histogram the bifurcation graph was drawn, the periodic orbits and topological invariants the local crossing number, relative rotation rates, and linking number during the process of period-doubting bifurcation and chaos were extracted. This study also examined the effect on the topological invariants when the sensitive parameters were varied. In addition, the topological invariants of a three-dimensional embedding of the strange attractor was extracted and the result was compared with those obtained from differential equations. This could be a new way for a state detection and fault diagnosis in a dynamical system.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.369-374
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• 2011

Generally the neural network and the Fuzzy compensative algorithms are applied to forecast the time series for power demand with the characteristics of a nonlinear dynamic system, but, relatively, they have a few prediction errors. They also make long term forecasts difficult because of sensitivity to the initial conditions. In this paper, we evaluate the chaotic characteristic of electrical power demand with qualitative and quantitative analysis methods and perform a forecast simulation of electrical power demand in regular sequence, attractor reconstruction and a time series forecast for multi dimension using Lyapunov Exponent (L.E.) quantitatively. We compare simulated results with previous methods and verify that the present method is more practical and effective than the previous methods. We also obtain the hourly predictability of time series for power demand using the L.E. and evaluate its accuracy.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.421-424
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• 2003

This paper proposes the generalized predictive control(GPC) method of chaotic systems using a self-recurrent wavelet neural network(SRWNN). The reposed SRWNN, a modified model of a wavelet neural network(WNN), has the attractive ability such as dynamic attractor, information storage for later use. Unlike a WNN, since the SRWNN has the mother wavelet layer which is composed of self-feedback neurons, mother wavelet nodes of the SRWNN can store the past information of the network. Thus the SRWNN can be used as a good tool for predicting the dynamic property of nonlinear dynamic systems. In our method, the gradient-descent(GD) method is used to train the SRWNN structure. Finally, the effectiveness and feasibility of the SRWNN based GPC is demonstrated with applications to a chaotic system.