• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.539-542
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• 2011

In this paper, we have implemented a performance analysis of $2{\times}1$ Alamouti scheme suggested by Alamouti, composed of the transmit space-time code and the simple linear decoding processing, in perfectly time-varying and spatially correlated channels. In addition, we derived the closed-form probability density function (PDF) of the output signal-to-noise ratio (SNR) and the outage probability of the Alamouti scheme as a function of the spatial correlation coefficient in the consideration of no correlation in time. As a result, it was found that the performance of the Alamouti scheme could be significantly degraded particularly in the case that the channels are time-varying and spatially correlated.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.697-712
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• 2013

When analyzing repeated binary data, the generalized estimating equations(GEE) approach produces consistent estimates for regression parameters even if an incorrect working correlation matrix is used. However, time-varying covariates experience larger changes in coefficients than time-invariant covariates across various working correlation structures for finite samples. In addition, the GEE approach may give biased estimates under missing at random(MAR). Weighted estimating equations and multiple imputation methods have been proposed to reduce biases in parameter estimates under MAR. This article studies if the two methods produce robust estimates across various working correlation structures for longitudinal binary data with time-varying covariates under different missing mechanisms. Through simulation, we observe that time-varying covariates have greater differences in parameter estimates across different working correlation structures than time-invariant covariates. The multiple imputation method produces more robust estimates under any working correlation structure and smaller biases compared to the other two methods.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.116-123
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• 2013

This paper represents generation of time-varying underwater acoustic channels by performing scattering simulation with time-varying ocean surface and Kirchhoff approximation. In order to estimate the time-varying ocean surface, 1D Pierson-Moskowitz ocean power spectrum and Gaussian correlation function were used. The computed scattering coefficients are applied to the amplitudes of each impulse of BELLHOP simulation result. The scattering coefficients are then compared with measured doppler spectral density of signal components which were scattered from ocean surface and the correlation time used in the Gaussian correlation function was estimated by the comparison. Finally, bit-error-rate and channel correlation simulations were performed with the generated time-varying channel based on passive time-reversal communication scenario.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.651-658
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• 2013

For the marginal model and generalized estimating equations (GEE) method there is important full covariates conditional mean (FCCM) assumption which is pointed out by Pepe and Anderson (1994). With longitudinal data with time-varying stochastic covariates, this assumption may not necessarily hold. If this assumption is violated, the biased estimates of regression coefficients may result. But if a diagonal working correlation matrix is used, irrespective of whether the assumption is violated, the resulting estimates are (nearly) unbiased (Pan et al., 2000).The quadratic inference functions (QIF) method proposed by Qu et al. (2000) is the method based on generalized method of moment (GMM) using GEE. The QIF yields a substantial improvement in efficiency for the estimator of ${\beta}$ when the working correlation is misspecified, and equal efficiency to the GEE when the working correlation is correct (Qu et al., 2000).In this paper, we interest in whether the QIF can improve the results of the GEE method in the case of FCCM is violated. We show that the QIF with exchangeable and AR(1) working correlation matrix cannot be consistent and asymptotically normal in this case. Also it may not be efficient than GEE with independence working correlation. Our simulation studies verify the result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.238-246
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• 2004

In this paper, an estimator that take advantages of time and frequency correlation within an OFDM symbol is investigated. OFDM systems using the proposed estimator can be very effective in detecting signals under non-sampled space and time-varying channels. Also, under same complexity, the proposed estimator outperforms the previously proposed estimator. Since even if there are no assumption about channel correlation, the linear interpolation method instead of optimal interpolation using correct channel correlation is proposed in case the receiver does not know the channel correlation function in time domain. Therefore the proposed channel estimator help improving the performance of OFDM systems under non-sampled spaced and fast time-varying channels.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.982-987
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• 2007

The necessity of data compression scheme for volume data has been increased because of the increase of data capacity and the amount of network uses. Now we have various kinds of compression schemes, and we can choose one of them depending on the data types, application fields, the preferences, etc. However, the capacity of data which is produced by application scientists has been excessively increased, and the format of most scientific data is 3D volume. For 2D image or 3D moving pictures, many kinds of standards are established and widely used, but for 3D volume data, specially time-varying volume data, it is very difficult to find any applicable compression schemes. In this paper, we present a compression scheme for encoding time-varying volume data. This scheme is aimed to encoding time-varying volume data for visualization. This scheme uses MPEG's I- and P-frame concept for raising compression ratio. Also, it transforms volume data using Daubechies D4 filter before encoding, so that the image quality is better than other wavelet-based compression schemes. This encoding scheme encodes time-varying volume data composed of single precision floating-point data. In addition, this scheme provides the random reconstruction accessibility for an unit, and can be used for compressing large time-varying volume data using correlation between frames while preserving image qualities.

• Communications for Statistical Applications and Methods
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• v.21 no.4
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• pp.335-347
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• 2014

This paper employs dynamic conditional correlation (DCC) model to examine time-varying comovement in the Korean stock market with a focus on the financial industry. Analyzing the daily returns of KOSPI 200 eight sector indices from January 2008 to December 2013, we find that stock market correlations significantly increased during the GFC period. The Financial Sector had the highest correlation between the Constructions-Machinery Sector; however, the Consumer Discretionary and Consumer Staples sectors indicated a relatively lower correlation between the Financial Sector. In terms of model fitting, the DCC with t distribution model concludes as the best among the four alternatives based on BIC, and the estimated shape parameter of t distribution is less than 10, implicating a strong tail dependence between the sectors. We report little asymmetric effect in correlation dynamics between sectors; however, we find strong asymmetric effect in volatility dynamics for each sector return.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.46-57
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• 1997

In this paper, we propose an efficient algorithm for adaptation of tracking windwo, which improves tracking performance of a correlation-based video tracker by rejecting background effect originated from a time-varying target. Th eproposed adaptation algorithm ajdusts the size of a tracking window by using the ratio of spatial gradient power in target region to that in backgorund region, which is especially adequate for a correlation-based tracker. Experimental results for synthetic and real image sequences show that the proposed method adapts a tracking window well to a time-varying target and so greatly suppresses background effect, which makes improvement of trakcing performance.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.476-479
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• 1995

A real time and adaptive method for obtaining Volterra kernels of a nonlinear system by use of pseudorandom M-sequences and correlation technique is proposed. The Volterra kernels are calculated real time and the obtained Volterra kernels becomes more accurate as time goes on. The simulation results show the effectiveness of this method for identifying time-varying nonlinear system.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.491-499
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• 2023

Scattering by Sea surface roughness occurs due to sea level roughness, communication performance deteriorates by causing frequency spread in communication signals and time variation in communication channels. In order to compare the difference in time variation of underwater acoustic communication channel according to the surface roughness, an experiment was performed in a tank owned by Hanyang University Ocean Acoustics Lab. Artificial surface roughness was created in the tank and communication signals with three bandwidths were used (8 kHz, 16 kHz, 32 kHz). The measured surface roughness was converted into a Rayleigh parameter and used as a roughness parameter, and statistical analysis was performed on the time-varying channel characteristics of the surface path using Doppler spread and correlation time. For the Doppler spread of the surface path, the Weighted Root Mean Square Doppler spread (w_fσ_ν) that corrected the effect of the carrier frequency and bandwidth of the communication signal was used. Using the correlation time of the surface path and the energy ratio of the direct path and the surface path, the correlation of total channels was simulated and compared with the measured correlation time of total channels. In this study, we propose a method for efficient communication signal design in an arbitrary marine environment by using the time-varying characteristics of the sea surface path according to the sea surface roughness.