• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.137-140
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• 1993

This paper describes a Chaos analyzer and its applications to characteristic analysis of ECG signals and the other signals. We can detect chaotic system among the various system by quantitative and qualitative analysis using the proposed system. And we also propose a new Possibility to recognize abnormal state of ECG signal using the chaotic characteristcs of signal.

• The Korean Journal of Financial Management
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• v.14 no.3
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• pp.183-201
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• 1997

본 논문은 우리나라의 주가지수수익률의 변동특성이 카오스를 내재하고 있는지 아니면 랜덤과정을 따르는지를 분석하기 위하여 Hurst의 R/S분석을 중심으로 분석하였다. 우리나라 증권시장의 1980년 1월 5일부터 1996년 말까지 총 4,982일 동안의 일별종합주가지수를 대수수익률로 전환한 시계열자료로 R/S분석한 결과 안정성과 주기유무를 판별하는 V-통계량 그래프에 의하면 83일과 33일의 비주기적 순환을 나타내고 있음을 알 수 있었다. 이러한 분석결과는 가우시안 랜덤과정과 그다지 큰 차이가 나지 않음을 알 수 있었다. 또한 선형성을 제거한 ARMA잔차와 비선형성을 제거한 GARCHM잔차자료에 대한 R/S분석한 결과도 원래 시계열보다 더 가우시안 랜덤과정에 더 근접함을 알 수 있었다. 한편 총 10개의 대리자료를 만들어서 평균을 취한 값으로 분석한 결과도 마찬가지로 나타나고 있다. 일별주가지수수익률에 내재하는 선형성분을 ARMA과정에 의정에 제거하고 남은 잔차중에는 비선형성분이 여전히 잔존하는데 그것이 일부 GARCHM과정에 의해서 미미하고 가우시안 랜덤과정이 보다 크게 나타남을 알 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.304-309
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• 2000

For understanding the information processing in human brain, we analyze the EEG, a spontaneous electric activity on the scalp of the human. In this paper, we used the mutual information to analyze EEG. The mutual information is used to show the stochastic correlation between signals which are generated in the communication and information theory. The used EEG is evoked by each auditory stimulus in positive and negative emotional states. As a result, we found thet there is some difference at the mutual information in each emotional state.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.215-219
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• 2000

인간의 뇌 정보처리를 이해하기 위한 일환으로서, 많은 연구자들이 사람의 두피에서 자발적으로 발생하는 전기 활동인 뇌파(EEG)를 분석하였다. 측정된 뇌파는 잡음처럼 보이는 비선형적인 거동으로 인하여 단순한 관찰만으로는 그 특징을 분석하기가 매우 어렵다. 따라서 이러한 뇌파를 분석하고 이해하기 위한 방법으로 파워스펙트럼, 바이스펙트럼 등과 같은 스펙트럼 분석과 상관차원, 프랙탈 차원과 같은 비선형 카오스 분석 등과 같은 해석법들이 활발히 연구되어왔다. 본 논문에서는 이러한 기존의 방법 외에 두 신호사이의 통계적 의존성을 측정하는 양인 상호정보를 이용하여 뇌파의 특징을 분석하였다. 뇌파간의 상호정보 분석을 통해 두뇌에서의 정보의 흐름에 관한 특징을 알아보았고, 감성자극에 반응하는 두뇌의 활동영역을 알 수 있었다.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.277-286
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• 2002

Genetic programming (GP) has been combined with quantum mechanical perturbation theory to make a new algorithm to construct mathematical models and perform predictions for chaotic time series from real world. Procedural similarities between time series modeling and perturbation theory to solve quantum mechanical wave equations are discussed, and the exemplary GP approach for implementing them is proposed. The approach is based on multiple populations and uses orthogonal functions for GP function set. GP is applied to original time series to get the first mathematical model. Numerical values of the model are subtracted from the original time series data to form a residual time series which is again subject to GP modeling procedure. The process is repeated until predetermined terminating conditions are met. The algorithm has been successfully applied to construct highly effective mathematical models for many real world chaotic time series. Comparisons with other methodologies and topics for further study are also introduced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.803-806
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• 2012

On this paper, various analysis methods has been applied to analyze and forecast the maximum electrical power needs, which is regarded as a nonlinear dynamic system. To understand the characteristic of complicated system, we used TISEAN package and evaluate the chaotic characteristic of time series obtained from electrical power demand using it. TISEAN package offers various algorithms and codes to analyze time series of nonlinear system effectively.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.153-166
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• 1998

본 연구에서는 도시 가로망에서의 구간 통행시간을 예측하기 위하여 time-frequency 분석의 일종인 웨이브렛변환과 RBF신경망 모형을 이용한 예측모형을 개발하였다. 웨이브렛 변환을 이용한 시계열 자료 분석을 통해서 통행시간에 내재되어 있는 다양한 패턴의 특징을 추출함으로써 오전/오후의 첨두현상, 신호교차로의 현시주기 등 주기적으로 발생되는 요인들에 의해서 통행시간 시계열 자료의 패턴에 나타나는 규칙성을 분석해 내었다. 분석된 패턴정보에 대한 규명은 카오스 이론을 근간으로한 시간지연좌표를 이용하여 시계열 자료의 규칙성을 시각적으로 판별하여 예측모형 구축에 활용하도록 하였다. 또, RBF신경망을 이용하여 예측범위의 공간적/시간적 확대에 따른 모형 구축에 소요되는 시간을 최소화하도록 하였으며, 시내버스 노선의 정류장간 운행시간 예측을 통해서 기존 연구에서 제기되었던 현실세계의 단순화, 다단계 예측시 정확성 등의 문제를 해결하였다. 예측실험결과 웨이브렛 변환을 데이터의 전처리 과정에 삽입하여 링크 통행시간의 패턴정보 예측에 활용할 경우, 기존의 예측모형에 비해서 훨씬 정확한 예측이 가능한 것으로 나타났으며, RBF 신경망은 짧은 학습시간에도 불구하고 역전파 신경망보다 우수한 예측력을 갖고 있는 것으로 밝혀졌다.

• Cross-Cultural Studies
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• v.41
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• pp.299-320
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• 2015

Lewis Carroll's Alice's Adventures in Wonderland expands scope of Children's Literature genre by introducing the discourse of pleasure as opposed to that of didactic discipline. Carroll's narrative is important, not only for children's literature, but also as a forerunner of post/modernism of James Joyce with its language play and linguistic invention. Its treatment of Alice's body change follows the motif of body transformation in myth and literature. Comparing "stasis" of Susan Sontag's character Alice (James) in her play Alice in Bed and "movement" of Carroll's Alice, this study explores the issues of woman's alienation and the dichotomy of mobility/immobility in reality and in their literary representations. Focusing on a female child's double alienation as woman and child, I argue Alice's Adventures in Wonderland is a counter-narrative of alternative bildungsroman. Alice gains her subjectivity through her adventure by power of language and story-telling. Through representation of the dream/adventure of two desiring sisters, Carroll's narrative exhibits subversion of social order and emergence of new order of "chaosmos" out of chaos. As a method of study, this study traces genealogy of "curiosity" in myth and literature as a motivating force that triggers adventure and argues "creative curiosity" is a dynamic energy propelling Alice's adventure.

• 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.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.786-791
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• 2007

Statistical differences between men and women are investigated for a total of eleven joint motions during level walking. Human locomotion which exhibits nonlinear dynamical behaviors is quantified by the chaos analysis. Time series of joint motions was obtained from gait experiments with ten young males and ten young females. Body motions were captured using eight video cameras, and the corresponding angular displacements of the neck and the upper body and lower extremity were computed by motion analysis software. The maximal Lyapunov exponents for eleven joints were calculated from attractors constructed and then were analyzed statistically by one-way ANOVA test to find any difference between the genders. This study shows that sexual differences in joint motions were statistically significant at the shoulder, knee and hip joints.