• The Journal of the Acoustical Society of Korea
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• v.10 no.2
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• pp.23-28
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• 1991

This paper is a study on isolated word recognition by independent speaker, we propose DTW speech recognition system by modified dynamic averaging method as reference pattern. 57 city names are selected as recognition vocabulary and 2th LPC cepstrum coefficients are used as the feature parameter. In this paper, besides recognition experiment using modified dynamic averaging method as reference pattern, we perform recognition experiments using causal method, dynamic averaging method, linear averaging method and clustering method with the same data in the same conditions for comparison with it. Through the experiment result, it is proved that recogntion rate by DTW using modified dynamic averaging method is the best as 97.6 percent.

• Journal of Environmental Science International
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• v.20 no.1
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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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• v.28 no.2
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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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• v.24 no.1
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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.

• Proceedings of the KIEE Conference
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• 1990.11a
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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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• v.16 no.1_2
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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.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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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.

• Korean Journal of Materials Research
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• v.33 no.5
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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.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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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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• v.8 no.2
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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.