• Korean Journal of Biological Psychiatry
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• v.5 no.1
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• pp.95-101
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• 1998

The changes of electroencephalogram(EEG) in patients with dementia of Alzheimer's type are most commonly studied by analyzing power or magnitude in traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to the chaos theory, irregular signals of EEG can be also resulted from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the largest Lyapunov exponent($L_1$). The authors have analyzed EEG epochs from three patients with dementia of Alzheimer's type and three matched control subjects. The largest $L_1$ is calculated from EEG epochs consisting of 16,384 data points per channel in 15 channels. The results showed that patients with dementia of Alzheimer's type had significantly lower $L_1$ than non-demented controls on 8 channels. Topographic analysis showed that the $L_1$ were significantly lower in patients with Alzheimer's disease on all the frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer's type have a decreased chaotic quality of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating the $L_1$ can be a promising tool for detecting relative changes in the complexity of brain dynamics.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.123-129
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• 2010

The purpose of study is to investigate the correlation between the Lyapunov exponent (LE) and the displacement of the center of gravity (DCG) for clarifying walking stability on the treadmill. From fifteen young healthy subjects volunteered, lower extremity joint angles were recorded using a three-dimensional motion capture system with reflective markers. The anteroposterior DCG and the LE were calculated by a commercial software. A linear correlation between LE and DCG (p<0.05) showed that LEs compensated for walking distance on the treadmill walking. However, LEs were found to be independent of self-selected walking speeds by a negligible correlation between LE and the Froude number (p>0.05).

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1691-1696
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• 2013

In this paper, an analysis of behavior is performed in the circular hybrid energy harvesting device. This analysis of behavior is to confirm with or without an existence of nonlinear system because its system is required to produce the more energy. To do this, first of all the phase portrait is reconstructed through Taken's embedding method, and then Poincare map is organized by using phase portrait and finally Lyapunov exponent is analyzed.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.315-319
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• 2001

A diagnosis system that provides early warnings regarding machine malfunction is very important for rolling mill so as to avoid great losses resulting from unexpected shutdown of the production line. But it is very difficult to provide e8rly w, ul1ings in rolling mill. Because dynamics of rolling mill is non-linear. This paper shows a chaotic behaviour of vibration signal in rolling mill using embedding method. Phase plane and Poincare map, FFT and histogram of vibration signal in rolling mill are implemented by qualitative analysis and Fractal dimension, Lyapunov exponent are presented by quantitative analysis.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.55-61
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• 2018

본 연구는 시각 동기 위상 측정 정보를 이용하여 전력계통에 나타나는 여러 가지 동요 현상을 검출하기 위한 기초 연구로써, 시계열 데이터 분석 분야로 분류된다. 제시한 방법은 비선형 동특성에 해석 기반으로 접근하여 전력계통에 나타날 수 있는 여러 동요 현상을 범용적으로 검출해 낼 수 있다. 비선형 동요 현상의 신호적 패턴을 수학적으로 기본 순시치 파형으로부터 피크치 샘플링을 통해 전개하여 계통 요소간 간섭으로 인한 원하지 않는 진동 모드를 검출하고자 한다. 계통의 변화로 진동 모드가 나타날 때, 2차원 평면에 실효치로 환산한 시계열 전압 데이터와 선형화된 플로퀘트 상수(Floquet multiplier)를 맵핑하여 도시하고, 정상상태 지점으로부터 거리를 계산하여 최대 리아프노프 지수 계산을 통해 계통이 불안정하게 되는 시간을 시계열 데이터 분석으로 추정하는 것이 본 방법의 핵심이다. 이러한 접근으로 제시한 비선형 동요 검출 알고리즘을 적용하여 디지털 필터 적용 또는 주파수 영역 해석과 같은 오프라인 Study와 달리 온라인으로 신속하게 계통의 현재 상태를 알 수 있게 된다.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2541-2543
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• 2001

회전체 베어링 상태진단에 신뢰성을 갖기 위하여 여러 가지 진단 방법이 연구되고 있으며, 이때 이용하는 변수는 온도와 소음, 진동 그리고 윤활유가 있으며 분석 방법으로는 온도추이분석, 소음분석, 진동분석, 윤활제 분석방법이 주로 이용되고 있다. 본 연구에서는 압연기 베어링의 상태진단의 변수로 베어링의 진동신호를 선택하고 이 진동신호에서 비선형성이 강한 신호 즉 카오스적 거동이 있음을 타켄스의 매립법과 포엔카레 단면, 상관차원과 리아프노프 지수를 이용하여 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.1
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• pp.28-33
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. The conventional methods for speech endpoint detection are based on two simple time-domain measurements-short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Accordingly, this algorithm is low complexity and suitable for Digital Isolated Word Recognition System.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.442-450
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• 2002

In measuring EEG, which is widely used for studying brain function, EEG is frequently mixed with noise and artifact. In this study, the signals relevant to the artifact were distracted by applying ICA to EEG signal. First, each independent component which was assumed to be the source was separated by applying ICA to EEG which involved artifact relevant to the eye movement of a normal person. Next, the signal which was assumed to be artifact was removed from the separated 18 independent components, and the nonlinear analysis method such as correlation dimension and the Iyapunov exponent was applied to each reconstructed EEG signal and the original signal including artifact in order to find meaningful difference between the two signals and infer the anatomical localization of its source and distribution. This study shows it is possible not only to analyze the brain function visually and spatially for visually complex EEG signal, but also to observe its meaningful change through the quantitative analysis of EEG by means of the nonlinear analysis.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.792-795
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• 2007

To quantify irregular body motions the time series analysis was applied to the gait study. The motions obtained from gait experiment are complex to exhibit nonlinear behaviors. The purpose of this study is to measure quantitatively the characteristics of the major six joints of the body during walking. The gait experiments were carried out for eighteen young males walking on a motor driven treadmill. Joint motions were captured using eight video cameras, and then three dimensional kinematics of the neck and the upper and lower extremities were computed by KWON 3D motion analysis software. The largest Lyapunov exponent was calculated from the time series to quantify stabilities of each joint. The results provides a data set of nonlinear dynamic characteristics for six joints engaged in normal walking.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.4
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• pp.8-17
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• 1998

Autonomous mobile robot agents(AMRAs) are robots which perform a given task by the same distributed self-organizing rules. In this paper, we let them form an equi-distance circle for the task of cooperative behaviors. Here, we suggest an algorithm to perform the taqk and then utilize a fuzzy system to improve the algorithm. It is shown that various cooperative activities appear in the simulation and particularly chaotic behaviors also appear by increasing the robot speed. Moreover, we prove the characteristics of this chaotic behaviors by calculating Lyapunov exponent.