• Journal of Communications and Networks
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• v.18 no.5
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• pp.762-772
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• 2016

This paper studies the problem of precoding and post-coding design for multicell multiuser downlink transmissions in the absence of perfect channel state information (CSI). Using statistical information of imperfect CSI, an iterative multiuser multicell transceiver design is formulated by minimizing the mean squared error (MSE) cost function of signal and leakage interference under per-base station power constraint (PBPC). The convergence of the iterative precoding and postcoding algorithm is verified by analytical and empirical results. The proposed precoding and postcoding algorithm offers a low computational complexity and robustness against CSI imperfection.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.29-31
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• 2013

본 논문에서는 기존라디오(primary) 네트워크와 스펙트럼을 공유하는(spectrum sharing) 인지라디오(cognitive radio) 네트워크에서 비재생적(non-regenerative) 다중안테나 중계 (relay) 시스템을 위한 소스(source) 및 중계기 프리코딩(precoding) 기법을 제안한다. 제안된 기법은 소스와 중계기 프리코딩 행렬의 최적해를 구하기 위해 QCQP(Quadratically Constrained Quadratic Programming) 문제를 통해 구한다. 제안된 기법은 기존라디오 수신기에서의 간섭세기 제한을 만족하면서 낮은 MSE(Mean squared error)와 높은 MI(Mutual Information)를 달성함을 모의실험결과를 통해 보인다. 또한 아주 빠른 속도로 최적해로 수렴함을 보이고 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.3
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• pp.193-203
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• 1988

In this paper, an echo canceller(EC) using decision feedback at the ISDN U-interface is presented and its performance based on the stochastic iteration algorithm is analyzed, and compared with the other conventional EC. The steady state mean-squared error(MSE) by the analytical resutls on the decision feedback-EC turns out to be smaller than that of the other linear EC. The performance of the ECs with the same convergence factor are almost the same regardless of different channel characteristics.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1249-1257
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• 2012

In this paper, we derive maximum likelihood estimators (MLEs) and approximate MLEs (AMLEs) of the unknown parameters in a generalized half logistic distribution when the data are upper record values. As an illustration, we examine the validity of our estimation using real data and simulated data. Finally, we compare the proposed estimators in the sense of the mean squared error (MSE) through a Monte Carlo simulation for various record values of size.

• Journal of Korean Society for Quality Management
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• v.38 no.4
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• pp.480-490
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• 2010

In this paper, two estimation methods(least square estimation and maximum likelihood estimation) were compared for Weibull distribution and Type I censoring. Data obtained by Monte Carlo simulation were analyzed using two estimation methods and analysis results were compared by MSE(Mean Squared Error). Comparison results show that maximum likelihood estimator is better for censored data and complete data with more than 30 samples and least square estimator is better for small size complete data(less than and equal to 20 samples).

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.283-291
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• 2003

The Gini index is one of the most commonly used measures of inequality of income distributions. In this paper, the Lorenz curve is estimated by arcs of two optimal circles, and a new simple method to estimate the Gini index is proposed using the law of cosines. We compare the proposed estimator with the estimator proposed by Ogwang and Rao(1996) in terms of the mean squared error(MSE) though Monte Carlo simulation in a Pareto distribution.

• Communications for Statistical Applications and Methods
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• v.20 no.1
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• pp.63-75
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• 2013

In this paper, we derive maximum likelihood estimators (MLEs) and approximate maximum likelihood estimators (AMLEs) of unknown parameters in a generalized half logistic distribution under Type-II hybrid censoring. We also obtain approximate confidence intervals using asymptotic variance and covariance matrices based on the MLEs and the AMLEs. As an illustration, we examine the validity of the proposed estimation using real data. Finally, we compare the proposed estimators in the sense of the mean squared error (MSE), bias, and length of the approximate confidence interval through a Monte Carlo simulation for various censoring schemes.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.345-346
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• 2007

In this paper, we propose a Pyramid VQ(PVQ) to quantize the transform coefficients of TCX module for the music improvement of AMR-WB+ codec. The proposed PVQ is compared to the $RE_8$ Lattice VQ used in the AHR-WB+ standard codec, demonstrating improvement 4% and 5.7%, respectively, in Mean Squared Error(MSE) and 3.3% and 4.7%, respectively, in Perceptual Evaluation of Audio Quality(PEAQ) by 8-dimensional and 16-dimensional Pyramid VQ.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.91-102
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• 2019

In this paper, we propose a new estimation method based on a weighted linear regression framework to obtain some estimators for unknown parameters in a two-parameter Rayleigh distribution under a progressive Type-II censoring scheme. We also provide unbiased estimators of the location parameter and scale parameter which have a nuisance parameter, and an estimator based on a pivotal quantity which does not depend on the other parameter. The proposed weighted least square estimator (WLSE) of the location parameter is not dependent on the scale parameter. In addition, the WLSE of the scale parameter is not dependent on the location parameter. The results are compared with the maximum likelihood method and pivot-based estimation method. The assessments and comparisons are done using Monte Carlo simulations and real data analysis. The simulation results show that the estimators ${\hat{\mu}}_u({\hat{\theta}}_p)$ and ${\hat{\theta}}_p({\hat{\mu}}_u)$ are superior to the other estimators in terms of the mean squared error (MSE) and bias.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.479-482
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• 2021

시계열 형태의 데이터는 다양한 분야에서 수집되고 응용되기 때문에 정확한 시계열 예측은 많은 분야에서 운영 효율성을 높일 수 있는 중요한 분석 방법으로 고려된다. 그중 다층 수평 예측은 사용자에게 전반적인 시계열 데이터 경향성을 제공할 수 있다. 하지만 다양한 정보를 포함하는 시계열 데이터는 데이터에 내재한 이질성(heterogeneity)까지 포괄적으로 고려한 방법을 통해서만 정확한 예측을 할 수 있다. 하지만 지금까지 많은 시계열 분석 모델들이 데이터의 이질성을 반영하지 못했다. 이러한 한계를 보완하고자 우리는 Temporal Fusion Transformer 모델을 사용하여 실생활과 밀접한 관련이 있는 데이터에 적용하여 이질성을 고려한 향상된 예측을 수행하였다. 실제, 주식 데이터와 미세 먼지 데이터와 같은 실생활 시계열 데이터에 적용하였고 실험 결과 기존 모델보다 Mean Squared Error(MSE)가 0.3487 낮은 것을 확인하였다.