• 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 and Information Engineers
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• v.51 no.5
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• pp.44-50
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• 2014

Chaos communication system is one of the security algorithms that is applied to improve the security. Chaos signal is non-linear, and it is generated randomly according to the initial conditions. Also, chaos communication system has characteristics such as non-periodic, wide-band, non-predictability of signals and easy implementation. So, security of chaos communication system is superior, and it has low interception probability and good anti-jamming characteristic. However, BER performance is worse than digital communication system, because it has many self interference signal in case of CDSK system. To improve these disadvantages, we analyze the PDF trend which can improve the BER performance in existing study, and we proposed a chaos map. And, proposed chaos map was defined as the 'Boss map'. Generally, BER performance is changed according to initial values, parameters and spreading factors. Therefore, in this paper, we will introduce PDF trends which can improve the BER performance, and will describe about Boss map. Also, characteristics of Boss map is analyzed by evaluating the BER performance of Boss map according to initial values, parameters and spreading factors. As a result, while maintaining the similar BER performance, initial value of Boss map can be selected from 0 to 1.2, and BER performance is best when parameter alpha is 2.5. Also, BER performance is best when spreading factor is 50.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.360-360
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• 2004

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.115-126
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• 1999

Past nears many Studies have been described for present state and forecasted for the future phenomena in various areas. Many theories and methodologies in transportation have been developed and applied by researchers and planners. On the other hand, many theories and methodologies had disappeared caused by their critical limitations. One of this cause that was discovered of the Chaos in traffic flows. The occurrence of Chaos in traffic flows has affected to the traffic volume and decreased significancy of a simulation result of a specific traffic flow. According to this fact, long-term forecast of traffic flow is difficult, moreover a butterfly effect impedes development and establishment of transportation model. A methodology to solve Chaos character in traffic flow can be able to provide more effective transport planning. This study tackles to enhance and revise the existing theories for the traffic flow applying Chaos theory to estimating travel time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6621-6629
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• 2014

Social phenomena require the fundamentals of novel scientific epistemology and methodology due to the continual change by complex variables. A systematic understanding of paradigm shifts is also necessary for analyzing the problems currently faced in society. This study presents chaos theory, which was developed from the natural sciences, to discuss the abnormality of modern society that underscores the importance of the chaos paradigm. Chaos theory is applicable to diverse social phenomena that stretches across politics, economics, and sociology. If social science research can appropriately and effectively develop and apply chaos theory, the theory can be utilized as a useful paradigm to reinforce the fundamentals of epistemology and methodology in exploring social phenomena.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.565-570
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• 2015

Spread spectrum communications have increased interest due to their immunity to channel fading and low probability of intercept. One of the limitations of the traditional digital spread spectrum systems is the need for spreading code synchronization. Chaotic communication is the analogue alternative of digital spread spectrum systems beside some extra features like simple transceiver structures. In this paper, This paper was used instead of the digital modulation and demodulation carriers for use in the chaotic signal in a digital communication system among the chaotic modulation schemes, the Differential Chaos Shift Keying(DCSK) is the most efficient one because its demodulator detects the data without the need to chaotic signal phase recovery. Also Implementation of Differential Chaos Shift Keying Communication System Using Matlab/Simulink and the receiver con decode the binary information sent by the transmitter, performance curves of DCSK are given in terms of bit-error probability versus signal to noise ratio with spreading factor as a parameter and we compare it to BPSK modulation.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.149-181
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• 2004

In this study we perform empirical tests using KOSPI return to investigate the existence of nonlinear characteristics in the generating process of stock returns. There are three categories in empirical tests; the test of nonlinear dependence, nonlinear stochastic process and nonlinear deterministic chaos. According to the analysis of nonlinearity, stock returns are not normally distributed but leptokurtic, and appear to have nonlinear dependence. And it's decided that the nonlinear structure of stock returns can not be completely explained using nonlinear stochastic models of ARCH-type. Nonlinear deterministic chaos system is the feedback system, which the past incidents influence the present, and it is the fractal structure with self-similarity and has the sensitive dependence on initial conditions. To summarize the results of chaos analysis for KOSPI return, it is the persistent time series, which is not IID and has long memory, takes biased random walk, and is estimated to be fractal distribution. Also correlation dimension, as the approximation of fractal dimension, converged stably within 3 and 4, and maximum Lyapunov exponent has positive value. This suggests that chaotic attractor and the sensitive dependence on initial conditions exist in stock returns. These results fit into the characteristics of chaos system. Therefore it's decided that the generating process of stock returns has nonlinear deterministic structure and follow chaotic process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.37-45
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• 2011

We studied noise influence on nonlinear chaotic system by using Logistic data series which is known as a typical nonlinear chaotic system. We regenerated Logistic data series by the method of adding noise according to noise level. And, we performed some analyses such as phase space reconstruction, correlation dimension, BDS statistics, and DVS Algorithms which are known as the methods of nonlinear deterministic or chaotic analysis. If we see the results of analysis, the characteristics of data series are gradually changed from nonlinear chaotic data series to random stochastic data series according to increasing noise level. We applied Low Pass Filter (LPF) and Kalman Filter techniques for the investigation of removing effect of the added noise to data series. Typical nonparametric method cannot distinguish nonlinear random series but the BDS statistic can distinguish the nonlinear randomness of the time series. Therefore this study used the BDS statistic which is well known as nonlinear statistical method for the investigation of randomness of time series for the effect of removing noise of data series. We found that Kalman filter is better method to remove the noise of chaotic data series even for high noise level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.697-700
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• 2005

최근들어 전력의 안정적인 공급과 계통의 안정한 운용 등을 위해서 신뢰성 높은 전력수요예측의 필요성이 점차 증가하고 있다. 본 논문에서는 기존에 제시된 예측시스템보다 정확도가 높은 전력수요예측을 위해 카오스 이론과 퍼지 보산 알고리즘을 이용하여 전력수요량 예측시스템을 제안한다. 최대수요 전력 시계열 데이터를 수집하여 카오스 성질을 분석하여 이를 바탕으로 퍼지 알고리즘을 적용한 전력수요량 예측 시스템을 구성하고, 이 시스템을 통하여 얻어진 결과와 실제 데이터를 비교함으로서 시스템의 성능을 평가한다.