• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.322-325
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• 1994

Mareel and Bitmead proved the presence of chaotic signal in random noise by applying dead beat control theory to adaptive mechanism. In this paper robust adaptive theory is proposed. With the property of chaotic signal that has order and law, the proposed theory can enhance the control Performance by applying the recursive algorithm that uses dynamic relation which have small correlation. The performance of proposed algorithm is demonstrated with the computer simulation of position control of electric motor. In this simulation, the adaptive low is adopted to control electric motor and the Presence of chaotic signal in feedback signal is proved by using several method such as time series, fourier spectrum phase portrait method.

• 한국정보처리학회논문지
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• 제3권4호
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• pp.877-882
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• 1996

Bonhoeffer-Van der Pol(BVP)모델을 실제 소자값을 이용하여 하드웨어를 구현하고 A1 coswt를 인가하여 주기 운동과 카오스 운동을 조사하였다. BVP모델의 하드웨어를 구성하기 위해 컴퓨터 시뮬레이션〔11〕에 의해 구현된 결과를 이용하여 실제 소자값 으로 Rescaling 하였으며 각 계수의 값을 a=0.7, b=0.8, c=0.1로 정하고 주기적 자극 전류의 진폭을 0에서 1.3까지 변화시켜 주기운동에서 카오스 운동으로 천이됨을 위 상공간, 시계열 데이터로 확인하였다.

• Journal of Information Technology Applications and Management
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• 제21권3호
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• pp.1-17
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• 2014

In this study, various characteristics of R&D related economic variables were studied to analyze complexity of science and technology activities in Korea, as reliance of R&D activities of the private sector is growing by the day. In comparison to other countries, this means that it is likely to be fluctuated by economic conditions. This complexity characteristic signifies that the result of science and technology activities can be greatly different from the anticipated results - depending on the influences from economic conditions and the results of science and technology activities which may be unpredictable. After reviewing the results of 17 variables related to science and technology characteristics of complex systems intended for time-series data - in the total R&D expenditure, and private R&D expenditure, numbers of SCI papers, the existence of chaotic characteristics were. using Lyapunov Exponent, Hurst Exponent, BDS test. This result reveals science and technology activity of the three most important components in Korea which are; heavy dependence on initial condition, the long term memory of time series, and non-linear structure. As stable R&D investment and result are needed in order to maintain steady development of Korea economy, the R&D structure should be less influenced by business cycles and more effective technology development policy for improving human resource development must be set in motion. And to minimize the risk of new technology, the construction of sophisticated technology forecasting system should take into account, for development of R&D system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1013-1016
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• 1993

This paper describes a new type of neuron model, the inputs of which are interfered with one another. It has a high mapping ability with only single unit. The learning speed is considerably improved compared with the conventional linear type neural networks. The proposed neuron model was successfully applied to the prediction problem of chaotic time series signal.

• 정보처리학회논문지B
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• 제9B권3호
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• pp.277-286
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• 2002

양자역학 섭동이론과 유전자프로그래밍(GP) 기법을 접목시킴으로써 실세계(Real-world)에서 발생하는 카오스 시계열에 대하여 수학모델을 구축, 예측하기 위한 새로운 알고리즘을 개발하였다. 시계열 분석과 양자역학 파동방정식의 해를 구하는 섭동이론과의 절차적 유사성을 논하고, 이것을 GP로 구현하는 전형적 접근방안을 제시한다. 함수집합(Function Set)으로서 직교함수(Orthogonal Functions)를 이용하고 병렬 집단을 사용하는 GP를 이용하여 원 시계열에 대한 초기 수학모델을 구하고, 원 시계열 데이터로부터 모델의 평가값을 뺀 나머지로 구성되는 잔여 시계열에 대하여 다시 GP를 적용하는 과정을 일정한 종료조건이 충족될 때가지 반복함으로써 실세계 카오스 시계열에 대한 정확성 높은 수학모델을 구축하는데 성공하였다. 타 방법론과의 비교와 향후 해결과제에 대하여도 소개한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.708-711
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• 1997

This paper proposes the hybrid algorithm for the optimization of the structure and parameters of the fuzzy neural networks by genetic algorithms (GA) to improve the behaviour and the design of fuzzy neural networks. Fuzzy neural networks have a distinguishing feature in that they can possess the advantage of both neural networks and fuzzy systems. In this way, we can bring the low-level learning and computational power of neural networks into fuzzy systems and also high-level, human like IF-THEN rule thinking and reasoning of fuzzy systems into neural networks. As a result, there are many research works concerning the optimization of the structure and parameters of fuzzy neural networks. In this paper, we propose the hybrid algorithm that can optimize both the structure and parameters of fuzzy neural networks. Numerical example is provided to show the advantages of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.627-629
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• 1997

In this paper, fuzzy logic system equipped with the back-propagation training algorithm as identifiers for nonlinear dynamic systems is described. To improve its performance, Jacob's delta-bar -delta rule is adapted in adjusting stepsize ${\alpha}$, and only y and ${\alpha}$ updating algorithm is suggested. In identifying and predicting the chaotic time series, suggested method is better than Li-Xin Wang's method,[1]

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 추계학술대회
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• pp.70-73
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• 1996

Many researchers had considered biological systems as linear systems. In many cases of biological systems, the phenomena that show the regular and periodic dynamics are considered the normal state. However, some clinical experiments reported, in some cases, the periodic signals represented the abnormal state. We assume that signals from human body system are generated from deterministic, intrinsic mechanisms and can be represented a simple equation that show nonlinear dynamics dependent on control parameters. The objective of our study is to model a nonlinear dynamics correctly from the nonlinear time series using the genetic programming method; to find a simple equation of nonlinear dynamics using collected time series and its nonlinear characteristics. We applied genetic programming to model RR interval of ECG that shows chaotic phenomena. We used 4 statistic measures and 2 fractal measures to estimate fitness of each chromosome, and could obtain good solutions of which chaotic features are similar.

• 정보기술과데이타베이스저널
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• 제6권1호
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• pp.73-88
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• 1999

There have been a series of debates to determine whether it would be possible to forecast dynamic systems such as stock markets. Recently the introduction of chaos theory has allowed many researchers to bring back this issue. Their main concern was whether the behavior of stock markets is chaotic or not. These studies, however, present divergent opinions on this question, depending upon the method applied and the data used. And the issue of predictability based on the nonlinear, chaotic nature was not dealt extensively. This paper is to test the nonlinear nature of the Korea stock market and accordingly attempts to predict its behavior. The result indicates that our stock market represents a chaotic behavior. We also found out based on our simulation that executing buy/sell transactions based upon forecasts which were derived using the local approximation method outperforms the decision of holding without a buy/sell transaction.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.110-113
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• 2003

In this paper, we propose that the chaotic behavior analysis in the mobile robot of embedding Arnold equation with obstacle. In order to analysis of chaotic behavior in the mobile robot, we apply not only qualitative analysis such as time-series, embedding phase plane, but also quantitative analysis such as Lyapunov exponent in the mobile robot with obstacle. In the obstacle, we only assume that all obstacles in the chaos trajectory surface in which robot workspace has an unstable limit cycle with Van der Pol equation.