• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.160-160
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• 2023

Generally, Global Climate Models (GCM) cannot be used directly due to their inherent error arising from over or under-estimation of climate variables compared to the observed data. Several bias correction methods have been devised to solve this problem. Most of the traditional bias correction methods are one dimensional as they bias correct the climate variables separately. One such method is the Quantile Mapping method which builds a transfer function based on the statistical differences between the GCM and observed variables. Laux et al. introduced a copula-based method that bias corrects simulated climate data by employing not one but two different climate variables simultaneously and essentially extends the traditional one dimensional method into two dimensions. but it has some limitations. This study uses objective functions to address specifically, the limitations of Laux's methods on the Quantile Mapping method. The objective functions used were the observed rank correlation function, the observed moment function and the observed likelihood function. To illustrate the performance of this method, it is applied to ten GCMs for 20 stations in South Korea. The marginal distributions used were the Weibull, Gamma, Lognormal, Logistic and the Gumbel distributions. The tested copula family include most Archimedean copula families. Five performance metrics are used to evaluate the efficiency of this method, the Mean Square Error, Root Mean Square Error, Kolmogorov-Smirnov test, Percent Bias, Nash-Sutcliffe Efficiency and the Kullback Leibler Divergence. The results showed a significant improvement of Laux's method especially when maximizing the observed rank correlation function and when maximizing a combination of the observed rank correlation and observed moments functions for all GCMs in the validation period.

• 산업기술연구
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• 제20권A호
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• pp.159-167
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• 2000

In the study rainfall frequency analysis attemped the many specific property data record duration it is differance from occur to error-term and probability ditribution of concern manifest. error-term analysis of method are fact sample data using method in other hand it is not appear to be fault that sample data of number to be small random variates. Therefore, day-rainfall data: to randomicity consider of this study sample data to the Monte Carlo method by randomize after data recode duration of form was choice method which compared an assumed maternal distribution from splitting frequency analysis consequence. In the conclusion, frequency analysis of chuncheon region rainfall appeared samll RMSE to the Gamma II distribution. In the rainfall frequency analysis estimate RMSE using random variates great transform, RMSE is appear that return period increasing little by little RMSE incresed and data number incresing to RMSE decreseing.

• 말소리와 음성과학
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• 제6권2호
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• pp.29-34
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• 2014

In the Vector Taylor Series (VTS)-based noisy speech recognition methods, Hidden Markov Models (HMM) are usually trained with clean speech. However, better performance is expected by training the HMM with noisy speech. In a previous study, we could find that Minimum Mean Square Error (MMSE) estimation of the training noisy speech in the log-spectrum domain produce improved recognition results, but since the proposed algorithm was done in the log-spectrum domain, it could not be used for the HMM adaptation. In this paper, we modify the previous algorithm to derive a novel mathematical relation between test and training noisy speech in the cepstrum domain and the mean and covariance of the Multi-condition TRaining (MTR) trained noisy speech HMM are adapted. In the noisy speech recognition experiments on the Aurora 2 database, the proposed method produced 10.6% of relative improvement in Word Error Rates (WERs) over the MTR method while the previous MMSE estimation of the training noisy speech produced 4.3% of relative improvement, which shows the superiority of the proposed method.

• 한국통신학회논문지
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• 제33권3A호
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• pp.256-268
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• 2008

본 논문에서는 다중 경로 레이리 페이딩 시변 채널 환경의 Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) 시스템에서 효율적으로 채널 변화를 추적할 수 있는 채널 추적방식을 제안하였다. 제안된 방식은 시변 채널에 대응할 수 있도록 블라인드 채널 예측기를 설계하였다. 또한 주파수 영역 채널 추정이 Minimum Mean Square Error (MMSE) 시간영역 채널 추정과 결합되어 있으며 이 방식은 매 OFDM 심벌마다 역행렬을 계산할 필요가 없다는 장점이 있다. 컴퓨터 시뮬레이션 결과 제안된 방식은 기존의 Li방식[4] 보다 성능이 우수함을 보였다. 도플러 주파수 100Hz 및 10-4 BER에서 Eb/No이득이 약 2.5 dB 정도 되었다. 도플러 주파수가 200Hz일 때 그 성능의 차이는 더욱 커졌다.

• 한국통신학회논문지
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• 제33권12A호
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• pp.1185-1190
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• 2008

이 논문에서는 IST (information society technologies)-WINNER (wireless world initiative new radio) 프로젝트에서 MU-MIMO (multiuser multiple-input multiple-output) 프리코딩 방식으로 채택된 SMMSE (successive minimum mean square error) 프리코딩 방법의 프리코딩 행렬 생성을 단순화하기 위한 $S^{2}MMSE$ (simplified SMMSE) 알고리즘을 제안한다. 기존의 알고리즘이 모든 사용자들의 모든 수신 안테나들을 대상으로 개별 MMSE nulling을 필요로 하는 프리코멍 벡터들을 생성하는 것과 대조적으로, 제안되는 알고리즘은 먼저 사용자 별 MMSE nulling 과정을 수행하고, 해당 사용자 내에서는 이 결과를 공통으로 이용하여 개별 수신 안테나에서 추가적인 MMSE nulling 과정 없이 단순한 행렬-벡터 곱으로 프리코딩 벡터를 계산한다. 따라서, 이 알고리즘을 사용하면 SMMSE 프리코딩을 위한 프리코멍 행렬 생성을 크게 단순화시킬 수 있다.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.421-436
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the deng's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(Wen's GRG & weighted mean) method is the best of any other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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• pp.55-62
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the dong's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute a missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(wen's GRG & weighted mean) method is the best of my other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• 지적과 국토정보
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• 제45권2호
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• pp.117-130
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• 2015

도근점측량과 같은 수평위치를 결정하는 방법 중 최소제곱법은 확률이론에 근거하여 잔차의 분산이 최소가 되는 조건을 만족하는 최확값을 산출하는 방법이다. 본 논문에서는 도선법으로 계산되는 현행 지적도근점측량의 성과와 최소제곱법을 적용한 도근점의 계산성과를 비교하고, 네트워크-RTK 측량결과와 각각의 조정방법에 대한 평균오차를 확인하였다. 실험 결과 최소제곱법이 도선법에 비해 폐합오차를 각 측점에 균등하게 배분하는 것을 확인하였으며, 네트워크-RTK 성과와의 평균오차도 도선법은 2.7cm, 최소제곱법은 2.2cm 산출되었다. 또한 과대오차가 발생한 경우 이를 확인하기 위한 방법으로 정방향 초기값과 역방향 초기값을 이용하여 수평각 과대오차를 확인할 수 있었으며, 관측된 측선거리와 계산된 측선 거리의 차이를 이용하여 거리 과대오차가 발생한 측선을 예측할 수 있었다.

• ETRI Journal
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• 제36권5호
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• pp.721-729
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• 2014

We propose a novel phase-based method for single-channel speech enhancement to extract and enhance the desired signals in noisy environments by utilizing the phase information. In the method, a phase-dependent a priori signal-to-noise ratio (SNR) is estimated in the log-mel spectral domain to utilize both the magnitude and phase information of input speech signals. The phase-dependent estimator is incorporated into the conventional magnitude-based decision-directed approach that recursively computes the a priori SNR from noisy speech. Additionally, we reduce the performance degradation owing to the one-frame delay of the estimated phase-dependent a priori SNR by using a minimum mean square error (MMSE)-based and maximum a posteriori (MAP)-based estimator. In our speech enhancement experiments, the proposed phase-dependent a priori SNR estimator is shown to improve the output SNR by 2.6 dB for both the MMSE-based and MAP-based estimator cases as compared to a conventional magnitude-based estimator.

• 대한의용생체공학회:의공학회지
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• 제16권2호
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• pp.239-248
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• 1995

The method of increasing signal to noise ratio (SNR) in a Hadamard transform spectrometer (HTS) is multiplexing. The multiplexing is executed by a mask. Conventional masks are mechanical or electro-optical. A mechanical mask has disadvantages of jamming and misalignment. A stationary electro-optical mask has a disadvantage of information losses caused by spacers which partition mask elements. In this paper, a mixed-concept electro-optical mask (MCEOM) is developed by expanding the length of a spacer to that of lon-off mask element. An MCEOM is operated by stepping a movable mask. 2N measurements are required for N spectrum estimates. The average mean square error (AMSE) using MCEQM is equal to that using a stationary electro-optical mask without spacers for large N. The cost of manufacturing an MCEOM is lower than that of producing a conventional electro-optical mask because an MCEOM needs only (N + 1)/2 on-off mask elements whereas the con¬ventional electro-optical mask needs N on-off mask elements. There are no information losses in the spectrometers having an MCEOM.