• The Journal of the Korea institute of electronic communication sciences
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• 제7권5호
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• pp.1073-1078
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• 2012

In this paper, we propose the MEMS system with Duffing equation to confirm nonlinear features in MEMS system. We also analyze nonlinear phenomena when adding the nonlinear term of another type. As a verification, we confirm chaotic motion by parameter variation through the time series, phase portrait and power spectrum.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제6권3호
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• pp.481-486
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• 2002

In this paper, we propose CELM(Cascade ELM) to improve stability. We could realize as cascade connected each other key value with N degree equation which has a initial value. And we could know to be improved in stability with the nature of Chaos in simulation result. In efficiency, this CELM algorithm identified sire of encrypted code with size of source code and we could know more efficient than existing RSA and ECC. In speed, CELM took average 0.18㎳ degree to encrypt a file. Although it was slower than DES, it was faster than ECC of RSA.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 한국산업정보학회 2003년도 추계공동학술대회
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• pp.449-467
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• 2003

뇌전도(EEG), 심전도(ECG) 와 같은 생체 전기신호는 카오스적 특성을 가지고 있으므로, 신호특성 분석에 비선형 도구를 사용하므로 의미있는 정보를 얻을 수 있다. 분석하는 데에는 주파수 특성, 변이 특성과 같은 생체시스템의 상태를 검증하는 방법이 주로 이용되어 왔다. 이에 본 연구에서는 심장 맥파의 RR 간격의 값을 획득하여 비선형 분석하는 도구로 Hurst Exponent 값의 변화를 모델화 하여 두 개의 비교대상 집단을 대상으로 차별성을 검출하는데 그 목적이 있다.

• Journal of the Korean Society for Precision Engineering
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• 제25권10호
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• pp.130-136
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• 2008

The purpose of this study was to investigate chaotic characteristics of major joint motions during treadmill walking. Gait experiments were carried out for 20 healthy young women. The subjects were asked to walk on a treadmill at their own natural speeds. The chaos analysis was used to quantify nonlinear motions of eleven major joints of each woman. The joints analyzed included the neck and the right and left shoulders, elbows, hips, knees and ankles. The recorded gait patterns were digitized and then coordinated by motion analysis software. Lyapunov exponent for every joint was calculated to evaluate joint characteristics from a state space created by time series and its embedding dimension. This study shows that differences in joint motion were statistically significant.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제30권2호
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• pp.194-201
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• 2006

Gait analysis is essential to identify accurate cause and knee condition from patients who display abnormal walking. Traditional linear tools can, however, mask the true structure of motor variability, since biomechanical data from a few strides during the gait have limitation to understanding the system. Therefore, it is necessary to propose a more precise dynamic method. The chaos analysis, a nonlinear technique, focuses on understand how variations in the gait pattern change over time. Eight healthy eight subjects walked on a treadmill for 100 seconds at 60 Hz. Three dimensional walking kinematic data were obtained using two cameras and KWON3D motion analyzer. The largest Lyapunov exponent from the measured knee angular displacement time series was calculated to quantify local stability. This study quantified the variability present in time series generated from gait parameter via chaos analysis. Knee flexion-extension patterns were found to be chaotic. The proposed Lyapunov exponent can be used in rehabilitation and diagnosis of recoverable patients.

• Knowledge Management Research
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• 제22권4호
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• pp.119-133
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• 2021

As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.

• Journal of Korea Water Resources Association
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• 제31권6호
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• pp.769-777
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• 1998

In this study, various time series are analyzed to check nonlinearities of the data. The nonlinearity of a system can be investigated by testing the randomness of the time series data. To test the randomness, four nonparametric test statistics and a new test statistic, called the BDS statistic are used and the results and the results are compared. The Brock, Dechert, and Scheinkman (BDS) statistic is originated from the statistical properties of the correlation integral which is used for searching for chaos and has been shown very effective in distinguishing nonlinear structures in dynamic systems from random structures. As a result of application to linear and nonlinear models which are well known, the BDS statistic is found to be more effective than nonparametric test statistics in identifying nonlinear structure in the time series. Hydrologic time series data are fitted to ARMA type models and the statistics are applied to the residuals. The results show that the BDS statistic can distinguish chaotic nonlinearity from randomness and that the BDS statistic can also be used for verifying the validity of the fitted model.

• Journal of the Korean Vacuum Society
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• 제21권5호
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• pp.249-257
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• 2012

Nonlinear dynamical behaviors of plasma in the Pierce diode are investigated by a numerical code developed using a one dimensional fluid model. The plasma in Pierce diode is alternately stable and unstable as Pierce parameter is changed. The dynamical characteristics of neutral and non-neutral Pierce system is examined analytically and numerically. It alternately has growing and oscillatory mode as Pierce parameter varies. As Pierce parameter is decreased, each oscillatory mode undergoes a sequence of subharmonic period-doubling bifurcation and then culminate in a chaotic strange attractor. The analysis for this nonlinear behavior can be used as a model for understanding of beam-plasma interaction in more complex geometries and a data for chaos control.

• Journal of the Institute of Convergence Signal Processing
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• 제9권1호
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• pp.89-97
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• 2008

Chaotic behavior in motor systems is undesired dynamics in real-time implementation since the speed is oscillated in a wide range and the torque is changed by a random manner. We present an adaptive control approach for time-varying permanent-magnet synchronous motors (PMSM) with chaotic phenomenon. We consider that its parameters are changed randomly within certain bounds. First, a nonlinear system model of a PMSM is transformed to derive a nominal linear control strategy. Then, an auxiliary control for compensating real-time control error occurred by system perturbation due to parameter change is designed by using Lyapunov stability theory. Numerical simulation is accomplished for evaluating its efficiency and reliability comparing with the traditional control method. Additionally, we test our control method in real-time motor experiment including a PSoC based drive system to demonstrate its practical applicability.

• The Journal of the Korea institute of electronic communication sciences
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• 제14권3호
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• pp.453-460
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• 2019

The SR-DCSK(Short Reference Differential Chaos Shift Keying) is a variant of DCSK that improves data transmission speed and energy efficiency without additional complexity. However, even when the reference signal of the optimum length is applied, the BER performance of the SR-DCSK is not better than that of the conventional DCSK. In this paper, we propose a scheme to improve the performance of SR-DCSK by applying two scale factors (scale coefficients) to the reference signal and the information signal, respectively. And the performance of the proposed method is analyzed by BER using Gaussian Approximation. Based on the derived BER expressions, we minimize the BER for a given system parameter to optimize the ratio of the two coefficients. Simulation results confirm that the BER of the proposed method is much improved over the SR-DCSK when we apply the optimal ratio of the two scale factors.