• Journal of the Korean Statistical Society
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• 제28권3호
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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.

• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.353-359
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• 1993

In this note we consider other type of tightness than that of Birkel (1988) and prove an invariance principle for nonstationary associated processes by an application of the central limit theorem of Cox and Grimmett (1984), thus avoiding the argument of uniform integrability. This result is an extension to the nonstationary case of an invariance priciple of Newman and Wright (1981) as well as an improvement of the central limit theorem of Cox and Grimmett (1984).

• 대한수학회논문집
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• 제12권2호
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• pp.411-418
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• 1997

In this note we prove a functional central limit theorem for nonstationary linearly positive quadrant dependent random fields. We extend it to the case of random measures.

• 전자공학회논문지A
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• 제32A권4호
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• pp.15-23
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• 1995

In this paper, we evaluate the performance of a transient queueing approximation when it is applied to modeling computer communication networks. An operational computer network that uses the ISO IS-IS(Intermediate System-Intermediate System) routing protocol is modeled as a Jackson network. The primary goal of the approximation pursued in the study was to provide transient queue statistics comparable in accuracy to the results from conventional Monte Carlo simulations. A closure approximation of the M/M/1 queueing system was extended to the general Jackson network in order to obtain transient queue statistics. The performance of the approximation was compared to a discrete event simulation under nonstationary conditions. The transient results from the two simulations are compared on the basis of queue size and computer execution time. Under nonstationary conditions, the approximations for the mean and variance of the number of packets in the queue erer fairly close to the simulation values. The approximation offered substantial speed improvements over the discrete event simulation. The closure approximation provided a good alternative Monte Carlo simulation of the computer networks.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.241-244
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• 2000

This paper addresses a new method of blind source separation (BSS) when sources are nonstationary signals. Our method requires only multiple correlation matrices of the observed data at several time-windowed data frames to estimate the mixing matrix. In contrast to most existing BSS methods where higher-order statistics is necessary, our method is based on only second-order statistics. In the framework of correlation matching, we develop a new BSS algorithm. The useful behavior of the proposed method is verified by numerical experiments.

• 응용통계연구
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• 제23권1호
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• pp.73-79
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• 2010

Missing values for unit root processes are imputed by the most recent observations. Treating the imputed observations as if they are complete ones, semiparametric unit root tests are extended to missing value situations. Also, an invariance principle for the partial sum process of the imputed observations is established under some mild conditions, which shows that the extended tests have the same limiting null distributions as those based on complete observations. The proposed tests are illustrated by analyzing an unequally spaced real data set.

• Communications for Statistical Applications and Methods
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• 제3권1호
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• pp.257-265
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• 1996

We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.

• 대한토목학회논문집
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• 제14권3호
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• pp.463-472
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• 1994

Random 지반운동에 대한 면진수조구조물 응답의 추계학적 해석방법을 연구하였다. 유연한 벽체와 내부유체간의 유체구조물 상호작용은 유체운동의 유한요소 모델링에 의하여 얻어지는 부가질량행렬 형태로 고려되었다. 정상(定常)(Stationary)지반운동으로는 수정된 Clough-Penzien Spectral Model이 사용되었으며, 비정상(非定常)(Nonstationary)지반운동으로는 상기모델에 포락함수를 적용한 모델을 사용하였다. 운동을 지배하는 Lyapunov Covariance Matrix 미분방정식의 해를 구하여 두 종류 면진시스템의 정상응답 및 비정상응답을 해석하였다.

• The Journal of the Acoustical Society of Korea
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• 제26권3E호
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• pp.87-96
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• 2007

In this paper we propose a new noise reduction algorithm for stationary and nonstationary noisy environments. Our algorithm classifies the speech and noise signal contributions in time-frequency bins, and is not based on a spectral algorithm or a minimum statistics approach. It relies on calculating the ratio of the standard deviation of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. We show that good quality can be achieved for enhancement speech signal by choosing appropriate values for ${\delta}_t\;and\;{\delta}_f$. The proposed method greatly reduces the noise while providing enhanced speech with lower residual noise and somewhat higher mean opinion score (MOS), background intrusiveness (BAK) and signal distortion (SIG) scores than conventional methods.

• The Journal of the Acoustical Society of Korea
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• 제27권1E호
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• pp.1-10
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• 2008

A noise suppression algorithm is proposed for nonstationary noisy environments. The proposed algorithm is different from the conventional approaches such as the spectral subtraction algorithm and the minimum statistics noise estimation algorithm in that it classifies speech and noise signals in time-frequency bins. It calculates the ratio of the variance of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. If the ratio is greater than an adaptive threshold, speech is considered to be present. Our adaptive algorithm tracks the threshold and controls the trade-off between residual noise and distortion. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of simplicity and light computational load for estimating the noise. This algorithm reduces the residual noise significantly, and is superior to the conventional methods.