• Journal of Advanced Navigation Technology
• /
• v.9 no.2
• /
• pp.140-146
• /
• 2005

In this paper, we proposed the frequency offset compensation algorithm and tracking algorithm which could improve the accumulated phase error for HDR-WPAN system. The proposed frequency offset compensation technique estimated each sample phase error by autocorrelation characteristics of CAZAC sequence, estimated phase error multiple each sample in a symbol, and finally compensated for the frequency offset. After frequency offset compensation using two steps, coarse and fine frequency offset, tracking algorithm have to use to compensate for the accumulated phase error. Because there is no pilot symbol in payload, more phase rotation occurred in received signal constellations due to the accumulated phase error as the payload length increase. Tracking algorithm compensates for a cumulative phase error ${\theta}$ between payload data.

• The Korean Journal of Applied Statistics
• /
• v.37 no.2
• /
• pp.191-207
• /
• 2024

Many studies have been conducted to quickly detect out-of-control situations in autocorrelated processes. The most traditionally used method is a residual control chart, which uses residuals calculated from a fitted time series model. However, many procedures for monitoring autocorrelated processes using statistical learning methods have recently been proposed. In this paper, we propose a monitoring procedure using the latent vector of LSTM Autoencoder, a deep learning-based unsupervised learning method. We compare the performance of this procedure with the LSTM Autoencoder procedure based on the reconstruction error, the RNN classification procedure, and the residual charting procedure through simulation studies. Simulation results show that the performance of the proposed procedure and the RNN classification procedure are similar, but the proposed procedure has the advantage of being useful in processes where sufficient out-of-control data cannot be obtained, because it does not require out-of-control data for training.

• Communications for Statistical Applications and Methods
• /
• v.1 no.1
• /
• pp.131-140
• /
• 1994

Box-Jenkins 시계열 분석에서 모형검진을 위한 통계량으로 잔차의 자기상관함수를 이용한 Box와 Pierce(1970)의 포트맨토우 검정과 Ljung과 Box(1978)의 변형된 포트맨토우 검정을 Basawa(1987)가 제안한 예측오차를 이용한 모형 검진 방법과 비교, 분석하였다. 시뮬레이션 연구를 수행하여 경험적 평균, 분산 및 유의 수준을 비교하여 과대적합의 방법을 이용하여 검정력을 비교하였다.

• The Korean Journal of Applied Statistics
• /
• v.29 no.1
• /
• pp.75-83
• /
• 2016

We propose methodology to analyze the dynamic mechanisms of financial market contagion under market integration using a biological contagion analytical approach. We employ U-statistic to measure market integration, and a dynamic model based on an error correction mechanism (single equation error correction model) and latent factor model to examine market contagion. We also use quantile regression and Wald-Wolfowitz runs test to test market contagion. This methodology is designed to effectively handle heteroscedasticity and correlated errors. Our simulation results show that the single equation error correction model fits well with the linear regression model with a stationary predictor and correlated errors.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.1
• /
• pp.54-69
• /
• 2021

Policy improvement such as the revision of the Road Traffic Act are proposed for personal mobility(especially e-scooter) usage. However, there is not enough discussion to solve the problem of using shared e-scooter. In this study, we analyze the influencing factors that amount of pick-up and drop-off of shared e-scooter by dividing the Seoul into a 200m grid. we develop spatial auotcorrelation model such as spatial lag model, spatial error model, spatial durbin model, and spatial durbin error model in order to consider the characteristics of the aggregated data based on a specific space, and the spatial durbin error model is selected as the final model. As a result, demographic factor, land use factor, and transport facility factors have statistically significant impacts on usage of shared e-scooter. The result of this study will be used as basic data for suggesting efficient operation strategies considering the characteristics of weekday and weekend.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.7A
• /
• pp.520-528
• /
• 2003

This paper proposes a method of implementing synthetic stereo and an acoustic echo cancellation algorithm for multiple participant conference system. Synthetic stereo is generated by HRTF and two loudspeakers. A robust adaptive algorithm for synthetic stereo echo cancellation is proposed to reduce the weight misalignment due to near-end speech signals and ambient noises. The proposed adaptive algorithm is modified version of SMAP algorithm and the coefficients of adaptive filter is updated with cross correlation of input and estimation error signal normalized with sum of the autocorrelation of input signal and the power of the estimation error signal multiplied with projection order. This is more robust to projection order and ambient noise than conventional SMAP. Computer simulation show that the proposed algorithm effectively attenuates synthetic stereo acoustic echo.

• The Korean Journal of Applied Statistics
• /
• v.31 no.2
• /
• pp.303-313
• /
• 2018

This study considers time series models to forecast drug expenditures in national health insurance. We adopt autoregressive error model (ARE) and transfer function model (TFM) with segmented level and trends (before and after 2012) in order to reflect drug price reduction in 2012. The ARE has only a segmented deterministic term to increase the forecasting performance, while the TFM explains a causality mechanism of drug expenditure with closely related exogenous variables. The mechanism is developed by cross-correlations of drug expenditures and exogenous variables. In both models, the level change appears significant and the number of drug users and ratio of elderly patients variables are significant in the TFM. The ARE tends to produce relatively low forecasts that have been influenced by a drug price reduction; however, the TFM does relatively high forecasts that have appropriately reflected the effects of exogenous variables. The ARIMA model without the exogenous variables produce the highest forecasts.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.36 no.4
• /
• pp.723-733
• /
• 2016

This study aims to analyze the effects of urban characteristics on the amount of damage caused by natural disasters. It is focused on the areas of a municipal level in Korea. Also, it takes into account the spatial autocorrelation of the damage caused by natural disasters. Moran's I statistics was estimated to examine the spatial autocorrelation in the damage from the study area. Subsequent to evaluating the suitability for spatial regression models and the OLS regression model, the spatial lag model was employed as an empirical analysis for the study. It showed that the increase in residential area leads to the decrease in the amount of natural disaster damage. On the other hand, the increase in green area and river basin is associated with the increase in the damage. As a result of empirical analysis, appropriate policy establishment and implementation about the damage-adding factors is needed in order to reduce the amount of damage in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.21 no.9
• /
• pp.995-1004
• /
• 2010

In the channel-varying environment, it is very important to estimate the signal to noise ratio(SNR) of received signal and to transmit the signal effectively for the modern communication system. The performance of existing non-data-aided (NDA) SNR estimation methods are substantially degraded for high level modulation scheme such as M-ary APSK or QAM. In this paper, we propose a SNR estimation method which uses zero point auto-correlation of received signal per block and auto-/cross- correlation of decision feedback signal in OFDM system. Proposed method can be studied into two Types; Type 1 can estimate SNR by zero point auto-correlation of decision feedback signal based on the second moment property. Type 2 uses both zero point auto-correlation and cross-correlation based on the fourth moment property. In block-by-block reception of OFDM system, these two SNR estimation methods can be possible for the practical implementation due to correlation based the estimation method and they show more stable estimation performance than the previous SNR estimation methods. Also, we mathematically derive the SNR estimation expression according to computational difference of auto-/cross-correlation. Finally, Monte Carlo simulations are used to verify the proposed method.

• Communications for Statistical Applications and Methods
• /
• v.17 no.2
• /
• pp.193-204
• /
• 2010

Recently, researchers of the various fields where the spatial analysis is needed have more interested in spatial statistics. In case of data with spatial correlation, methodologies accounting for the correlation are required and there have been developments in methods for spatial data analysis. Lattice data among spatial data is analyzed with following three procedures: (1) definition of the spatial neighborhood, (2) definition of spatial weight, and (3) the analysis using spatial models. The present paper shows a spatial statistical analysis method superior to a general statistical method in aspect estimation by using the trimmed mean squared error statistic, when we analysis the spatial lattice data that outliers are included. To show validation and usefulness of contents in this paper, we perform a small simulation study and show an empirical example with a criminal data in BusanJin-Gu, Korea.