• 한국음향학회지
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• 제10권2호
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• pp.23-28
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• 1991

본 논문을 특정화자에 대한 단독어 음성 인식에 대한 연구이다. 우리는 표준패턴으로서 변형된 dynamic linear averaging 방법을 이용한 DTW 음성 인식 시스템을 제안한다. 57개의 모든 도시명이 인식 대상 어휘로 선정되었고 12차 LPC cepstram 계수를 특징계수로 사용하였다. 이 논문은 표준패턴으로 변형된 dynamic linear averaging 방법을 이용하여 인식 실험을 한것 이외에도 같은 데이터 같은 조건상에서 causal 방법과 dynamic averaging방법, linear averaging방법, clustering 방법을 이용하여 실험하였다. 실험결과로 변형시킨 dynamic linear averaging 방법을 이용한 DTW 음성인식이 97.6%로 가장 좋은 인식율을 보였다.

• 한국환경과학회지
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• 제20권1호
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• pp.107-118
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• 2011

While the assessment of mean flow field is very important to characterize the hydrodynamic aspect of the flow regime in river, the conventional methodologies have required very time-consuming efforts and cost to obtain the mean flow field. The paper provides an efficient technique to quickly assess mean flow field by developing and applying spatial averaging method utilizing repeatedly surveyed acoustic Doppler current profiler(ADCP)'s cross-sectional measurements. ADCP has been widely used in measuring the detailed velocity and discharge in the last two decades. In order to validate the proposed spatial averaging method, the averaged velocity filed using the spatial averaging was compared with the bench-mark data computed by the time-averaging of the consistent fix-point ADCP measurement, which has been known as a valid but a bit inefficient way to obtain mean velocity field. The comparison showed a good agreement between two methods, which indicates that the spatial averaging method is able to be used as a surrogate way to assess the mean flow field. Bed shear stress distribution, which is a derived hydrodynamic quantity from the mean velocity field, was additionally computed by using both spatial and time-averaging methods, and they were compared each other so as to validate the spatial averaging method. This comparison also gave a good agreement. Therefore, such comparisons proved the validity of the spatial averaging to quickly assess mean flow field. The mean velocity field and its derived riverine quantities can be actively used for characterizing the flow dynamics as well as potentially applicable for validating numerical simulations.

• Communications for Statistical Applications and Methods
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• 제28권2호
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• pp.189-204
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• 2021

In a regression analysis, a single best model is usually selected among several candidate models. However, it is often useful to combine several candidate models to achieve better performance, especially, in the prediction viewpoint. Model combining methods such as stacking and Bayesian model averaging (BMA) have been suggested from the perspective of averaging candidate models. When the candidate models include a true model, it is expected that BMA generally gives better performance than stacking. On the other hand, when candidate models do not include the true model, it is known that stacking outperforms BMA. Since stacking and BMA approaches have different properties, it is difficult to determine which method is more appropriate under other situations. In particular, it is not easy to find research papers that compare stacking and BMA when regression model assumptions are violated. Therefore, in the paper, we compare the performance among model averaging methods as well as a single best model in the linear regression analysis when standard linear regression assumptions are violated. Simulations were conducted to compare model averaging methods with the linear regression when data include outliers and data do not include them. We also compared them when data include errors from a non-normal distribution. The model averaging methods were applied to the water pollution data, which have a strong multicollinearity among variables. Simulation studies showed that the stacking method tends to give better performance than BMA or standard linear regression analysis (including the stepwise selection method) in the sense of risks (see (3.1)) or prediction error (see (3.2)) when typical linear regression assumptions are violated.

• Communications for Statistical Applications and Methods
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• 제24권1호
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• pp.67-80
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• 2017

Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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• pp.352-356
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• 1990

In this paper proposed a new analysis method that can be controlled DC separately excited motor using DC chopper. An analysis method can be broadly divided the state variables method and the state space averaging method. The state variable method is largely used for analysis method in the time area, but it is complicated analysis of the nonlinear circuit and modeling of the system. Therefore a boundary of the current continuous mode and discontinuous mode can be definited by the state space averaging method. Also this paper proposed a new approximation analysis method using state space averaging method in the discontinuous mode.

• Journal of applied mathematics & informatics
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• 제16권1_2호
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• pp.497-507
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• 2004

In this paper, we first seek the equivalent statements with averaging properties in terms of the regular summability method, secondly define some new averaging properties and study their implications. Finally, we investigate the question of what property is dual to the Banach-Saks property suggested by C. Seifert.

• 한국군사과학기술학회지
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• 제2권2호
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• pp.157-165
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• 1999

Production and measurement of a super-polished few-ppm-scattering mirror substrate are investigated. In order to improve the surface roughness directly determining scattering, the super-polishing process using Bowl-Feed technique is tried. The surface quality of the super-polished substrate is estimated by the phase-measuring interferometer. For the reliable roughness measurement using the interferometer, data averaging method is applied so that the optimal data averaging condition, 30 phase-data averaging and 20 intensity-data averaging, minimizing the measurement error is experimently searched. Based on the optimal data averaging condition, surface roughness of home-made mirror substrate is measured to be less than $0.5{\AA}$ rms corresponding to 2-ppm total-integrated-scattering.

• 한국재료학회지
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• 제33권5호
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• pp.205-213
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• 2023

This paper reports the results of an experimental examination using X-rays to test annealing materials for lapped bearing steel (STB2), to confirm the validity of the weighted averaging analysis method. The distribution behavior for the α_𝜓-sin²𝜓 diagram and the presence or absence of differences in the peak method, half-value breadth method, and centroid method were investigated. When lapping the annealed bearing steel (STB2) material, a residual stress state with a non-directional steep gradient appeared in the surface layer, and it was found that the weighted averaging analysis method was effective. If there is a steep stress gradient, the sin²𝜓 diagram is curved and the diffraction intensity distribution curve becomes asymmetric, resulting in a difference between the peak method, half-value breadth method, and centroid method. This phenomenon was evident when the stress gradient was more than 2~3 kg/mm²/㎛. In this case, if the position of the diffraction line is determined using the centroid method and the weighted averaging analysis method is applied, the stress value on the surface and the stress gradient under the surface can be obtained more accurately. When the stress gradient becomes a problem, since the curvature of the sin²𝜓 diagram appears clearly in the region of sin²𝜓 > 0.5, it is necessary to increase the inclination angle 𝜓 as much as possible. In the case of a lapping layer, a more accurate value can be obtained by considering 𝜎₃ in the weighted averaging analysis method. In an isotropic biaxial residual stress state, the presence or absence of 𝜎₃ can be determined as the presence or absence of strain for sin²𝜓≈0.4.

• 전자공학회논문지S
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• 제34S권3호
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• pp.55-62
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• 1997

For the effective removal of artifacts and the extraction of an improved evoked potential response, we propose the averaging method usin gthe shrinkag eof wavelet coefficients. The wavelet analysis decomposes the measured evoked potentials into scale coefficients with low frequency components and wavelet coefficients with high ones as a resolution level, respectively. and in the course of synthesis evoked potentials, the presented method shrinks the wavelet coefficients, and then reproduces the evoked potentials, and lastly averages it. We measured visual evoked potentials to simulate the averaging method using the shrinkage of wavelet coefficients, and compared it with aveaged signal. As a result of simulations, the proposed method gets improved VEP about 0.2-1.6dB in comparison with the averaging method with daubechies wavelet in the resolution level four.

• Industrial Engineering and Management Systems
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• 제8권2호
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• pp.93-100
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• 2009

In this paper, we review widely used methods to extract local volatility surfaces (LVSs) from implied volatility surfaces (IVSs) and suggest a model averaging method for constructing implied and local volatility surfaces weighted by trading volumes. It makes use of model averaging method by means of bandwidth priors, and then produces a robust LVS estimation. The method is shown to provide the information about the confidence interval of estimators as well as a rather less variable weighted mean value for the IVS and LVS. To show the merits of our proposed method, we conduct simulations on equity-linked warrants (ELWs) with reasonable and acceptable results.