• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.279-285
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• 2002

In this paper we consider the problem of testing for structural changes in ARIMA models based on a cusum test. In particular, the proposed test procedure is applicable to testing for a change of the status of time series from stationarity to nonstationarity or vice versa. The idea is to transform the time series via differencing to make stationary time series. We propose a graphical method to identify the correct order of differencing.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.97-100
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• 2003

This paper addresses a method of convolutive source separation that based on SEONS (Second Order Nonstationary Source Separation) [1] that was originally developed for blind separation of instantaneous mixtures using nonstationarity. In order to tackle this problem, we transform the convolutive BSS problem into multiple short-term instantaneous problems in the frequency domain and separated the instantaneous mixtures in every frequency bin. Moreover, we also employ a H infinity filtering technique in order to reduce the sensor noise effect. Numerical experiments are provided to demonstrate the effectiveness of the proposed approach and compare its performances with existing methods.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.281-286
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• 2003

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive process to determine whether or not a time series is stationary. The tests have an exact binomial null distribution and are robust to the outliers and the heteroscedastic errors. Monte-Carlo simulation shows that the sign test is locally more powerful than the OLSE-based tests for heavy-tailed and/or heteroscedastic error distributions.

• The Journal of the Acoustical Society of Korea
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• v.12 no.1E
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• pp.56-64
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• 1993

본 논문은 공간적으로 변하는 스펙트럼을 추정하는 새로운 적응 방법을 제안한다. 제안한 방법에서는 오래된 upstream의 데이터를 망각함으로서 신호의 nonstationarity를 고려해주는 시변망각인자의 개념을 recursive least square(RLS) 알고리즘에 도입하였으며, 관심이 있는 공간영역에서 탐사침을 천천히 움직여 얻은 하나의 데이터 군으로부터 downstream 스펙트럼을 추정하였다. 제시한 방법의 실현 가능성은 실제 실험(wind tunnel 이용)을 통해서 얻은 공간적으로 변하는 nonstatonary 신호의 스펙트럼을 추정하는 과정에서 입증되며 또한 기존의 방법들과 비교함으로서 그 우수성을 보인다.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.89-96
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• 2015

In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.83-91
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• 2005

We analyze the performance of an adaptive hybrid search code acquisition algorithm for direct-sequence code division multiple access (DS-CDMA) systems under slowly-moving mobile environments. The code acquisition algorithm is designed to provide the desired feature of constant false alarm rate (CFAR) to cope with nonstationarity of the interference in CDMA forward links. An analytical expression for the mean acquisition time is first derived and the probabilities of detection, miss, and false alarm are then obtained for frequency-selective Rayleigh fading environments. The fading envelope of a received signal is assumed to be constant over the duration of post-detection integration (PDI), considering slow fading environments. Finally, the performance of the designed code acquisition algorithm shall be evaluated numerically to examine the effect of some design parameters such as the sub-window size, size of the PDI, decision threshold, and so on, considering cdma2000 environments.

• Earthquakes and Structures
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• v.16 no.5
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• pp.563-573
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• 2019

When generating spectrum-compatible artificial ground motion in engineering practices, the effect of the variation in fitting parameters on the distribution of the peak ground displacement (PGD) has not yet drawn enough attention. In this study, a method for simulating ground motion matching for multiple targets is developed. In this method, a frequency-dependent amplitude envelope function with statistical parameters is introduced to simulate the nonstationarity of the frequency in earthquake ground motion. Then, several groups of time-history acceleration with different temporal and spectral nonstationarities were generated to analyze the effect of nonstationary parameter variations on the distribution of PGD. The following conclusions are drawn from the results: (1) In the simulation of spectrum-compatible artificial ground motion, if the acceleration time-history is generated with random initial phases, the corresponding PGD distribution is quite discrete and an uncertain number of PGD values lower than the limit value are observed. Nevertheless, the mean values of PGD always meet the requirement in every group. (2) If the nonstationary frequencies of the ground motion are taken into account when fitting the target spectrum, the corresponding PGD values will increase. A correlation analysis shows that the change in the mean and the dispersion values, from before the frequencies are controlled to after, correlates with the modal parameters of the predominant frequencies. (3) Extending the maximum period of the target spectrum will increase the corresponding PGD value and, simultaneously, decrease the PGD dispersion. Finally, in order to control the PGD effectively, the ground motion simulation method suggested in this study was revised to target a specified PGD. This novel method can generate ground motion that satisfies not only the required precision of the target spectrum, peak ground acceleration (PGA), and nonstationarity characteristics of the ground motion but also meets the required limit of the PGD, improving engineering practices.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.37-43
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• 1998

This paper proposes a new echo canceller that can be used in a full-duplex digital subscriber loop modem. The proposed echo canceller uses a NLMS-based parallel adaptation NLMS (PA-NLMS) algorithm. The PA-NLMS algorithm that an estimate of the nonstationarity to additive noise ratio (NNR) gained from two distinct NLMS processes is used to select the value of NLMS convergence-controlling parameter has been developed. Numerical results based on computer simulation show that the proposed algorithm has a convergence rate approaching that of the fastest possible NLMS process while improving on its MAC performance considerably.

• Journal of the Korean Statistical Society
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• v.28 no.3
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• pp.371-387
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• 1999

For possibly nonstationary autoregressive moving average, modeling based on the original observations rather than the differenced observations is considered. Under this scheme, sample autocorrelation functions, parameter estimates, model diagnostic statistics, and prediction are all computed from the original data instead of the differenced data. The methods and results established under stationarity of data are shown to naturally extend to the nonstationarity of one autoregressive unit root. The sample ACF and PACF can be used for ARMA order determination. The BIC order is strongly consistent. The parameter estimates are asymptotically normal. The portmanteau statistic has chi-square distribution. The predictor is asymptotically equivalent to that based on the differenced data.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1450-1454
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• 2006

Empirical mode decomposition (EMD) is applied to analyze time series characterized with nonlinearity and nonstationarity. This decomposition could be utilized to construct finite and small number intrinsic mode functions (IMF) that describe complicated time series, while admitting the Hilbert transformation properties. EMD has the capability of being adaptive, capture local characteristics, and applicable to nonlinear and nonstationary processes. Unlike discrete wavelet transform (DWT), IMF eliminates spurious harmonics and retains meaningful instantaneous frequencies. Examples based on data representing natural phenomena are given to demonstrate highlight the power of this method in contrast and comparison of other ones. A presentation of the energy-frequency-time distribution of these signals found to be more informative and intuitive when based on Hilbert transformation.