• 전기학회논문지
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• 제63권2호
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• pp.291-296
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• 2014

Most of the statistical signal analysis processed in the time domain and the frequency domain are based on the assumption that the signal is weakly stationary(wide sense stationary). Therefore, it is necessary to know whether the surface EMG signals processed in the statistical basis satisfy the condition of weak stationarity. The purpose of this study is to analyze the accuracy of the Run-test, modified Run-test, RA(reverse arrangement)-test, and modified RA-test for assessing surface EMG signal stationarity. Six stationary and three non-stationary signals were simulated by using sine wave, AR(autoregressive) modeling, and real surface EMG. The simulated signals were tested for stationarity using nine different methods of Run-test and RA-test. The results showed that the modified Run-test method2 (mRT2) classified exactly the surface EMG signals by stationarity with 100% accuracy. This finding indicates that the mRT2 may be the best way for assessing stationarity in surface EMG signals.

• 전기학회논문지
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• 제63권8호
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• pp.1128-1133
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• 2014

Most of the statistical signal analysis processed in the time domain and the frequency domain are based on the assumption that the signal is weakly stationary(wide sense stationary). Therefore, it is necessary to know whether the surface EMG signals processed in the statistical basis satisfy the condition of the weak stationarity. The purpose of this study is to find optimal segment length of surface EMG signal for assessing stationarity with the modified Run-test and RA-test. Ten stationary surface EMG signals were simulated by AR(autoregressive) modeling, and ten real surface EMG signals were recorded from biceps brachii muscle and then modified to have non-stationary structures. In condition of varying segment length from 20ms to 100ms, stationarity of the signals was tested by using six different methods of modified Run-test and RA-test. The results indicate that the optimal segment length for the surface EMG is 30ms~35ms, and the best way for assessing surface EMG signal stationarity is the modified Run-test (Run2) method using this optimal length.

• 대한인간공학회지
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• 제29권4호
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• pp.667-671
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• 2010

Runs test is a mathematical tool to test the stationarity of electromyographic (EMG) signals. The purpose of this study is to investigate the effects of segmentation size on the stationarity of EMG signals in runs test. Six subjects participated in this experiment and performed isometric trunk exertions for twenty seconds at the load level of 25% and 50% MVC. The signals extracted from the erector spinae muscles were divided into the intervals of 1000ms and the stationarity of the signal in each interval was tested by the runs test. In this test, seven segmentation sizes such as 1.0, 2.0, 3.9, 7.8, 15.6, 31.3 and 62.5ms were applied. Additionally, two stationarity tests of reverse arrangements test and modified reverse arrangements test were used to verify the results of the runs test. In results, the segmentation size of 62.5ms showed the similar results with the other stationarity tests. However, the stationarity values among there tests were different each other when segmentation sizes other than 62.5ms were used. These results indicated the effect of segmentation size in runs test that needs to be considered to have consistent and sensitive result in stationarity test.

• 대한인간공학회지
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• 제29권2호
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• pp.183-188
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• 2010

The purpose of this study is to investigate the stationarity of the electromyographic signal in various flexion angles, loads, and window sizes, which influence the result of the mean power frequency (MPF) and median frequency (MNF) analysis. Six healthy subjects participated in the experiment. They were tested in the combination of 3-level flexion angles (0 degree, 22.5 degree, 45 degree) and 3-level loads (0Nm, 30Nm, 60Nm). Electromyographic data were collected for 20 seconds during isometric contraction. The stationarity of collected data were analyzed with four different window sizes including 250, 500, 1000 and 2000ms. Two test methods for stationarity such as Reverse Arrangements Test and Modified Reverse Arrangements Test were used. In order to show the effect of nonstationarity, the increasing/decreasing trend of MPF and MNF trend were discussed. In results, the stationarity of the electromyographic signal decreased as flexion angle increased and load decreased while window size decreased based on Reverse Arrangements Test. The highest stationarity was shown at 500 ms window in Modified Reverse Arrangements Test. The inclination of MNF and MPF indicated 3.6-6.3%, 3.8-5.1% discrepancy compared to the result from stationary data.

• 응용통계연구
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• 제22권3호
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• pp.499-513
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• 2009

An economic signal in the real world usually reflects complex phenomena. One may have difficulty both extracting and interpreting information embedded in such a signal. A natural way to reduce complexity is to decompose the original signal into several simple components, and then analyze each component. Spectral analysis (Priestley, 1981) provides a tool to analyze such signals under the assumption that the time series is stationary. However when the signal is subject to non-stationary and nonlinear characteristics such as amplitude and frequency modulation along time scale, spectral analysis is not suitable. Huang et al. (1998b, 1999) proposed a data-adaptive decomposition method called empirical mode decomposition and then applied Hilbert spectral analysis to decomposed signals called intrinsic mode function. Huang et al. (1998b, 1999) named this two step procedure the Hilbert-Huang transform(HHT). Because of its robustness in the presence of nonlinearity and non-stationarity, HHT has been used in various fields. In this paper, we discuss the applications of the HHT and demonstrate its promising potential for non-stationary financial time series data provided through a Korean stock price index.

• International Journal of Contents
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• 제3권2호
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• pp.35-39
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• 2007

The cognitive radio communication is taking the attentions because the development of the technique came to be possible to analyze wireless signals. In the IEEE 802.22 WRAN Systems[1], how to detect a spectrum and signals is continuously studied. In this paper, we propose the efficient signal detection method using SCF (Spectral Correlation Function). It is easy to detect the signal feature when we are using the SCF. Because most modulated signals have the cyclo-stationarity which is unique for each signal. But the fading channel effected serious influence even though it detects the feature of the signal. We applied LMS(Least Mean Square) filter for the compensation of the signal which is effected the serious influence in the fading channel. And we analyze some signal patterns through the SCF. And we show the unique signal feature of each signal through the SCF method. It is robust for low SNR(Signal to Noise Ratio) environment and we can distinguish it in the fading channel using LMS Filter.

• 마케팅과학연구
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• 제16권1호
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• pp.13-26
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• 2006

본 연구에서는 안정적 NBD모형에 개별구매자들의 평균적 구매율 변화로 발생되는 임의의 불안정성이 개입하였는지를 체계적으로 검정하기 위한 방법을 개발하였다. 이를 위해 본 연구에서는 안정적 NBD모형에서 개별구매자들의 갖는 평균적 구매율이 임의의 불안정성의 영향으로 구조적 변화를 일으키는지에 대한 통계적 가설로부터 우도비를 도출하였다. 또한, 본 연구에서는 반복구매가 이루어지는 패널자료를 대상으로 개발된 ㅂ아법의 실증적 적합성을 살펴보았다. 본 연구의 결과는 NBD모형이 지니는 안정성의 가정을 극복할 수 있는 수단을 제공한다는 점, 마케팅환경의 변화를 조기에 감지함으로써 관련 환경변화에 신속히 대처할 수 있는 마케팅전략의 운용을 가능케 할 것이란 점, 특정 마케팅믹스전략의 효과측정에도 활용될 수 있다는 점 등을 기대할 수 있다.

• Wind and Structures
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• 제24권1호
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• pp.59-78
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• 2017

Non-stationarity and non-Gaussian property are two of the most important characteristics of wind. These two features are studied in this study based on wind speed records measured at different heights from a 325 m high meteorological tower during the synoptic wind storms. By using the time-frequency analysis tools, it is found that after removing the low frequency trend of the longitudinal wind, the retained fluctuating wind speeds remain to be asymmetrically non-Gaussian distributed. Results show that such non-Gaussianity is due to the weak-stationarity of the detrended fluctuating wind speed. The low frequency components of the fluctuating wind speeds mainly contribute to the non-zero skewness, while distribution of the high frequency component is found to have high kurtosis values. By further studying the decomposed wind speed, the mechanisms of the non-Gaussian distribution are examined from the phase, turbulence energy point of view.

• 대한전자공학회논문지TC
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• 제45권12호
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• pp.152-158
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• 2008

천해 환경에서 정합필터와 LFM(linear frequency modulation) 펄스를 사용하는 능동소나의 탐지성능은 비백색잡음인 잔향에 의해 크게 저하될 수 있다. 이 경우 잔향의 영향을 줄이기 위해 일반적으로 정합필터에 선행하여 백색화 필터를 사용한다. 기존에는 탐지 블록과 선행 블록의 잔향이 통계적으로 정상성을 유지한다고 가정하고 선행 블록의 잔향 특성을 이용하여 탐지 블록의 잔향을 추정하고 백색화 하였다. 잔향의 정상성은 인접 블록 사이뿐만 아니라 좀더 넓은 범위에서 유지될 수 있다. 이 경우 더 많은 인접 블록을 이용하면 탐지 블록의 잔향을 더 정밀하게 추정할 수 있을 것이다. 본 논문에서는 실제 해안에서 획득한 잔향 신호를 분석하여 적절한 추정 블록의 범위를 구한다. 그리고 추정 블록의 범위에 따른 선-백색화 정합필터의 성능을 비교, 분석한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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• pp.2435-2453
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• 2015

Independent component analysis (ICA) is a signal processing technique used for un-mixing of the mixed recorded signals. In wireless communication, ICA is mainly used in multiple input multiple output (MIMO) systems. Most of the existing work regarding the ICA applications in MIMO systems assumed static or quasi static wireless channels. Performance of the ICA algorithms degrades in case of time varying wireless channels and is further degraded if the data block lengths are reduced to get the quasi stationarity. In this paper, we propose an ICA based MIMO transceiver that performs well in time varying wireless channels, even for smaller data blocks. Simulation is performed over quadrature amplitude modulated (QAM) signals. Results show that the proposed transceiver system outperforms the existing MIMO system utilizing the FastICA and the OBAICA algorithms in both the transceiver systems for time varying wireless channels. Performance improvement is observed for different data blocks lengths and signal to noise ratios (SNRs).