• 한국산학기술학회논문지
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• 제19권7호
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• pp.16-23
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• 2018

카오스는 비선형 과학 분야에서 매우 중요한 주제 중의 하나이며, Lorenz가 처음으로 소개한 이후 집중적으로 연구되어지고 있다. 카오스 시스템의 한 특성은 카오스 시스템에 의해 생성된 신호는 다른 어떤 시스템과 동기화되지 않는다는 것이다. 따라서 두 카오스 시스템은 서로 동기화되는 것이 불가능한 것처럼 보이지만, 만약 두 시스템이 적절한 방법으로 정보를 교환한다면 이 두 시스템은 동기화가 가능하다. 본 논문에서는 능동 제어와 슬라이딩 모드 제어, 그리고 리아프노프 안정도 이론을 기반으로 하는 변형된 Lorenz 카오스 시스템의 동기화 문제에 대해 다룬다. 동기화를 위해 고려한 기법은 선형상태 오차 변수에 의해 짝을 이룬 구동시스템과 응답시스템으로 구성된다. 이를 위해 우선 대상 카오스 시스템에 대해 간단히 살펴본다. 다음으로 능동제어, 슬라이딩 모드 제어 기법을 이용한 카오스 시스템의 동기화와 채터링 문제를 해결하기 위한 제어 방법을 도출한다. 전체 폐루프 시스템의 점근적 안정도는 리아프노프 안정도 이론에 의해 증명한다. 컴퓨터 시뮬레이션은 제안한 방법의 타당성을 확인하기 위해 그래픽으로 제시한다.

• 한국정보처리학회논문지
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• 제6권5호
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• pp.1312-1322
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• 1999

The world of linearity, which is regular, predictable and irrelevant to time sequence in most natural phenomenon, is a very small part. In fact, signals generated from natural phenomenon with which we're in contact are showed only slight linearity. Therefore it is very difficult to understand and analyze natural phenomenon with only predictable and regular linear systems. Due to these reasons researches concerning non-linear signals that of analysis were excluded being regarded as noise are being actively carried out. Countless signals generated from nonlinear system have the information about itself, and analyzing those signals and get information from it, that will be able to be used effectively in so may fields. Hence, in this paper we used a higher order spectrum, especially the bispectrum. After we prove the validity applying bispectrum to logistic map, which is typical chaotic signal. Subsequently by showing the result applying for actual signal analysis of EEG according to auditory stimuli, we show that higher order spectra is a very useful parameter in analysis of non-linear signals and the result of EEG analysis according to auditory stimuli.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.853-856
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• 1993

In this paper, we describe a chaos simulator as a developing tool for applications of chaos engineering. This simulator is composed of three modules, such as generation module of chaotic signals by deterministic rules, determination module whether observed time series is chaos or not, and nonlinear system identification module by self generating Neuro Fuzzy Model.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.294-297
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• 2002

We investigate the dynamics of a non-autonomous chaotic oscillator including an optocoupler that shows a periode-doubling and a chaos dynamics under any conditions of input circuit via experiments. Its characteristics was found to coincide input frequency components with output's. But, the relationship between input signals and output signals is different according to the amplitude of driving input voltage and circuit structure. Thus, this result can be applied to a wide variety of optical systems in the future.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 C
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• pp.1606-1608
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• 2001

In connection with the monitoring of the insulation degradation of the large power apparatus, a statistical treatment, such as phase resolved partial discharge analysis (PRPDA) has been established for the on-line monitoring system during the past two decades. However, it has shown some inconveniences to distinguish the nature of the PD source in power apparatus. In this regard, a novel approach based on the chaotic analysis(CAPD) is proposed describing the fundamental ideas, outcomes and different view points from conventional PRPDA. In order to make a model for the possible defects causing sudden failures in service, several types of specimen were prepared. And partial discharge signals, originated from those samples, were measured and analyzed by means of PRPDA and CAPD respectively. In this paper, it seems that the correlation between the consecutive PD pulses depending on the nature of PD could be investigated by CAPD. Therefore, it could be considered that the nature of PD source can be distinguished more distinctively when the PRPDA is combined with CAPD.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 춘계학술대회 논문집 유기절연재료 전자세라믹 방전플라즈마 연구회
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• pp.221-224
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• 2001

In connection with the monitoring of insulation degradation of large power apparatus in order to predict their unexpected service failures, a statistical treatment, such as phase resolved partial discharge analysis(PRPDA), has been established for the on-line monitoring system during the past decades. However, this method has shown some inconveniences to distinguish the nature of the PD source in power apparatus. In this regard, a novel approach based on the chaotic analysis(CAPD) is proposed describing the fundamental ideas, outcomes and different view points from conventional PRPDA. In order to make a model for the possible defects causing sudden failures in service, several types of specimen were prepared. And partial discharge signals, originated from those samples, were measured and analysed by means of PRPDA and CAPD respectively. Throughout this paper, it seems that the correlation between the consecutive PD pulses depending on the nature of PD could be investigated by CAPD. Therefore, it could be considered that the nature of PD source can be distinguished more distinctively when the PRPDA is combined with CAPD.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• 한국컴퓨터정보학회논문지
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• 제16권2호
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• pp.201-206
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• 2011

디지털 디스플레이어의 보급과 발달로 인하여 기존의 인쇄용 액자보다 디지털 액자에 대한 관심이 높아지고 있다. 우리는 이런 디지털 액자를 정적인 자료 디스플레이용도 뿐만 아니라 CCD 카메라와 조합하여 감시용 모니터링 장비로 활용하기 위한 새로운 LCD 전자 액자를 개발하였다. 개발된 액자는 감시용 화상 데이터의 보안을 위해 기존의 양방향 통신암호화를 대체하여 단방향 통신 암호화 방법으로 개발 하였다. 이 방법은 혼돈계의 단방향 동기화현상을 이용한 것으로 일정 시간 동안 동기화를 진행 시키면 어느 시점에서든 암호화와 복호화를 시킬 수 있는 방법으로 양방향 통신 암호화와 같은 결과를 얻을 수 있다. 또한, 우리가 제시한 이 방법을 유비쿼터스 기기의 근거리 통신방법에 적용한다면 보다 효율적인 결과를 얻을 수 있을 것으로 생각된다.

• 대한의용생체공학회:의공학회지
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• 제29권4호
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• pp.329-336
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• 2008

Recently, causality analysis of source time series extracted from EEG or MEG signals is becoming of great importance in human brain mapping studies and noninvasive diagnosis of various brain diseases. Two approaches have been widely used for the analyses: one is independent component analysis (ICA), and the other is multiple signal classification (MUSIC). To the best of our knowledge, however, any comparison studies to reveal the difference of the two approaches have not been reported. In the present study, we compared the performance of the two different techniques, ICA and MUSIC, especially focusing on how accurately they can estimate and separate various brain electrical signals such as linear, nonlinear, and chaotic signals without a priori knowledge. Results of the realistic simulation studies, adopting directed transfer function (DTF) and Granger causality (GC) as measures of the accurate extraction of source time series, demonstrated that the MUSIC-based approach is more reliable than the ICA-based approach.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 하계학술대회 논문집 Vol.3 No.2
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• pp.939-944
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• 2002

PD phenomena can be regarded as a deterministic dynamical process where PD should be occurred if the local electric field be reached to be sufficiently high. And thus, its mathematical model can be described by either difference equations or differential equations using several state variables obtained from the time sequential measured data of PD signals. These variables can provide rich and complex behavior of detectable time series, for which Chaos theory can be employed. In this respect, a new PD pattern recognition method is proposed and named as 'Chaotic Analysis of Partial Discharges (CAPD)' for this work. For this purpose, six types of specimen are designed and made as the models of the possible defects that may cause sudden failures of the underground power transmission cables under service, and partial discharge signals, generated from those samples, are detected and then analyzed by means of CAPD. Throughout the work, qualitative and quantitative properties related to the PD signals from different defects are analyzed by use of attractor in phase space, information dimensions ($D_0$ and D2), Lyapunov exponents and K-S entropy as well. Based on these results, it could be pointed out that the nature of defect seems to be identified more distinctively when the CAPD is combined with traditional statistical method such as PRPDA. Furthermore, the relationship between PD magnitude and the occurrence timing is investigated with a view to simulating PD phenomena.