• 한국통신학회논문지
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• 제33권12A호
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• pp.1138-1146
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• 2008

This paper considers 2-hop wireless cooperative communications networks with fixed decode-and-forward relays. Specifically, we first derive the closed-form BER expression for theoretically evaluating the end-to-end performance of these networks. Then, based on this expression and long-tenn fading statistics, we propose a power allocation method for source and relay. Such a method brings about multiple advantages in tenn of spectral efficiency and implementation complexity over other power allocation methods based on instantaneous fading statistics. A variety of numerical results reveal that the cooperative communications scheme with the proposed power allocation significantly outperforms that with the equal power allocation and the direct transmission scheme for any position of the relay subject to the same total transmit power constraint.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.411-421
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• 2023

This paper provides a new estimation equation based on the concept of a minimum distance between the empirical and theoretical distribution functions under the most widely used progressive Type-II censoring scheme. For illustrative purposes, simulated and real datasets from a three-parameter Weibull distribution are analyzed. For comparison, the most popular estimation methods, the maximum likelihood and maximum product of spacings estimation methods, are developed together. In the analysis of simulated datasets, the excellence of the provided estimation method is demonstrated through the degree of the estimation failure of the likelihood-based method, and its validity is demonstrated through the mean squared errors and biases of the estimators obtained from the provided estimation equation. In the analysis of the real dataset, two types of goodness-of-fit tests are performed on whether the observed dataset has the three-parameter Weibull distribution under the progressive Type-II censoring scheme, through which the performance of the new estimation equation provided is examined.

• 한국음향학회지
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• 제30권3호
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• pp.123-128
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• 2011

본 논문에서는 다양한 잡음 환경에서 음성향상을 위한 Minimum Statistics (MS) 잡음전력 추정 기법을 제시한다. 기존의 방법에서는 최소값 추적을 위해서 유한한 서치 (search)윈도우를 사용하여 최적으로 신호의 파워 스펙트럼을 수무딩하고 최소 확률을 적용하는 것을 기본으로 한다. 본 논문에서 제안된 알고리즘은 기존의 최소값 서치 윈도우가 다양한 잡음 환경에 상관없이 고정된 사이즈를 사용하는 것에 환경인식 정보를 적용하여 서치 윈도우 사이즈가 Gaussian mixture model(GMM)기반의 잡음 분류 알고리즘을 이용한 결과 값의 비교로 잡음 환경에 따라 변화 하도록 한다. 제안된 음성 향상 기법은 ITU-T P.862 perceptual evaluation of speech quality (PESQ)를 이용하여 평가하였고 기존의 MS방법보다 향상된 결과를 보였다.

• 방송공학회논문지
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• 제26권2호
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• pp.184-196
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• 2021

본 논문은 객체 검출 알고리즘을 위한 통계치 적응적인 선형 회귀 기반 객체 크기 예측 방법을 제안한다. 기존에 제안된 딥 러닝 기반 객체 검출 알고리즘 중 YOLOv2 및 YOLOv3은 객체의 크기를 예측하기 위하여 네트워크의 마지막 계층에 통계치 적응적인 지수 회귀 모델을 사용한다. 하지만, 지수 회귀 모델은 역전파 과정에서 지수 함수의 특성상 매우 큰 미분값을 네트워크의 파라미터로 전파시킬 수 있는 문제점이 있다. 따라서 본 논문에서는 미분 값의 발산 문제를 해결하기 위하여 객체 크기 예측을 위한 통계치 적응적인 선형 회귀 모델을 제안한다. 제안하는 통계치 적응적인 선형 회귀 모델은 딥러닝 네트워크의 마지막 계층에 사용되며, 학습 데이터셋에 존재하는 객체들의 크기에 대한 통계치를 이용하여 객체의 크기를 예측한다. 제안하는 방법의 성능 평가를 위하여 YOLOv3 tiny를 기반으로 제안하는 방법을 적용하여 재설계한 네트워크의 검출 성능과 YOLOv3 tiny의 검출 성능을 비교하였으며, 성능 비교를 위한 데이터셋으로는 UFPR-ALPR 데이터셋을 사용하였다. 실험을 통해 제안하는 방법의 우수성을 검증하였다.

• 응용통계연구
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• 제23권1호
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• pp.41-47
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• 2010

본 연구에서는 재무 시계열 자료를 분석하는데 있어 유용하게 쓰이는 이분산성 시계열 모형하에서 이상치 탐지 기법을 적용하여 그 효율성을 보이고자 한다. 먼저 GARCH 모형과 GARCH 모형하에서 이상치 탐지 기법에 대해 소개하고, 적용된 방법이 기존의 전통적인 이상치 탐지 방법보다 성능이 우수함을 시뮬레이션과 실제 KOSPI 자료에 적합시켜 입증하였다.

• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.415-422
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• 2012

본 연구에서는 단기에 측정되는 트래픽 자료를 예측하기 위하여 Holt-Winters, Fractional Seasonal ARIMA, AR-GARCH, Seasonal AR-GARCH 모형을 사용하여 각 모형의 예측 성능을 비교하고자 한다. 예측에 이용된 시계열 모형에 대해 소개하고, 실제 트래픽 자료에 적용하여 트래픽 자료를 분석한 결과 Holt-Winters방법이 예측력 측면에서 가장 우수하였다.

• 전기학회논문지
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• 제56권3호
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• pp.629-631
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• 2007

In hands-free full-duplex communication systems, acoustic signals picked up by the microphones can be mixed with echo signals as well as noises, which may result in poor performance of the corresponding communication system. Also, the system performance may decrease further if the reverberation occurs since it is harder to estimate the impulse response of the demixing system. For blind source separation (BSS) in such cases, a time-frequency masking approach can be employed to separate undesired echo signals and noises, but, permutation ambiguities also should be solved for the echo cancellation. In this paper, we propose a new acoustic echo cancellation (AEC) approach utilizing the time-frequency masking and higher-order statistics, whereby a desired signal selection, based on coherence and third-order statistics (i.e., kurtosis), is introduced along with output signal normalization. Simulation results demonstrate that the proposed approach yields better echo and noise cancellation performances than the conventional AEC approaches.

• Communications for Statistical Applications and Methods
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• 제16권2호
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• pp.383-388
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• 2009

In this paper we propose a variance function estimation method based on kernel trick for replicated data or data consisted of sample variances. Newton-Raphson method is used to obtain associated parameter vector. Furthermore, the generalized approximate cross validation function is introduced to select the hyper-parameters which affect the performance of the proposed variance function estimation method. Experimental results are then presented which illustrate the performance of the proposed procedure.

• 품질경영학회지
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• 제37권2호
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• pp.46-57
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• 2009

The traditional approach to economic design of control charts is based on the assumption that a process is monitored using a performance variable. However, various types of automatic test equipments recently introduced as a part of factory automation usually measure surrogate variables instead of performance variables that are costly to measure. In this article we propose a model for economic design of a control chart which uses a surrogate variable that is highly correlated with the performance variable. The optimum values of the design parameters are determined by maximizing the total average income per cycle time. Numerical studies are performed to compare the proposed $\bar{X}$ control charts with the traditional model using the examples in Panagos et al. (1985).

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.65-77
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• 2020

Geometric charts are effective in monitoring the fraction nonconforming in high-quality processes. The in-control fraction nonconforming is unknown in most actual processes; therefore, it should be estimated using the Phase I sample. However, if the Phase I sample size is small the practitioner may not achieve the desired in-control performance because estimation errors can occur when the parameters are estimated. Therefore, in this paper, we adjust the control limits of geometric charts with the bootstrap algorithm to improve the in-control performance of charts with smaller sample sizes. The simulation results show that the adjustment with the bootstrap algorithm improves the in-control performance of geometric charts by controlling the probability that the in-control average run length has a value greater than the desired one. The out-of-control performance of geometric charts with adjusted limits is also discussed.