• Korean Journal of Remote Sensing
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• v.28 no.5
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• pp.549-559
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• 2012

This paper presents a comparative analysis on the applicability of a priori statistic information about adjustment models when the surface shape parameters are estimated at an arbitrary point in an elevation data. Although the reliability of the estimates are known to be affected by surface condition and the adjustment models, there has been little research in a systematic and detail way. When the raw data have been taken from a real measurement, its true value cannot be known, however, thus this study used simulation data in order to analyze clearly the applicability of adjustment models. The generation of simulated data was performed by superimposing horizontal, slope, and curve surfaces and adding a certain amount of noise. Comparative analysis was performed by associating the a posteriori estimates with a priori statistics of each adjustment models. The experimental results show the estimation characteristics of adjustment models against varying surface conditions.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.10
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• pp.1255-1263
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• 2004

An a priori test has been conducted for the dynamic mixed model which was generalized for the prediction of passive scalar field in a turbulent channel flow The results from a priori tests indicated that dynamic mixed model is capable of predicting both subgrid-scale heat flux and dissipation rather accurately. The success is attributed to the explicitly calculated resolved term incorporated into the model. The actual test of the model in a LES a posteriori showed that dynamic mixed model is superior to the widely used dynamic Smagorinsky model in the prediction of temperature statistics.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.77-83
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• 2009

This paper proposes a new noise-biased compensation of minimum statistics(MS) method using a nonlinear function and a priori speech absence probability(SAP) for speech enhancement in non-stationary noisy environments. The minimum statistics(MS) method is well known technique for noise power estimation in non-stationary noisy environments. It tends to bias the noise estimate below that of true noise level. The proposed method is combined with an adaptive parameter based on a sigmoid function and a priori speech absence probability (SAP) for biased compensation. Specifically. we apply the adaptive parameter according to the a posteriori SNR. In addition, when the a priori SAP equals unity, the adaptive biased compensation factor separately increases ${\delta}_{max}$ each frequency bin, and vice versa. We evaluate the estimation of noise power capability in highly non-stationary and various noise environments, the improvement in the segmental signal-to-noise ratio (SNR), and the Itakura-Saito Distortion Measure (ISDM) integrated into a spectral subtraction (SS). The results shows that our proposed method is superior to the conventional MS approach.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.23-37
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• 2011

In this paper, we use a modified Tikhonov regularization method to solve the Fredholm integral equation of the first kind. Under the assumption that measured data are contaminated with deterministic errors, we give two error estimates. The convergence rates can be obtained under the suitable choices of regularization parameters and the number of measured points. Some numerical experiments show that the proposed method is effective and stable.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.85.1-85.1
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• 2019

Accurate estimation of the masses, the ages, and the chemical abundances of host stars is crucial to understand physical characteristics of exo-planetary systems. In this study, we investigate physical dimensions of 94 planet-hosting stars based on spectroscopic observation and stellar evolutionary computation, From the high resolution echelle spectroscopy of the BOES observation, we have analysed metallicities and alpha-element enhancements of host stars. By combining recent spectro-photometric observations, stellar parameters are calibrated within the frame work of the standard stellar theory. In general, the minimum chi-square estimation can be strongly biased in cases that stellar properties rapidly changes after the terminal age main-sequence. Instead, we adopt a Bayesian statistics considering a priori distribution of stellar parameters during the rapid evolutionary phases. we determine a reliable set of stellar parameters between theoretical model grids. To overcome this statistical bias, (1) we adopt a Bayesian statistics considering a priori distribution of stellar parameters during the rapid evolutionary phases and (2) we construct the fine model grid that covers mass range ($0.2{\sim}3.0M_{\odot}$) with the mass step ${\Delta}M=0.01M_{\odot}$, metallicities Z = 0.0001 ~ 0.04, and the helium and the alpha-element enhancement. In this presentation, we introduce our calibration scheme for several hosting stars.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.32-41
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• 1999

In this paper, an inversion method using chirp signals and two near field receivers is proposed. Inversion problems can be formulated into the probabilistic models composed of signals, a forward model and noise. Forward model to simulate chirp signals is chosen to be the source-wavelet-convolution planewave modeling method. The solution of the inversion problem is defined by a posteriori pdf. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the ranges for a priori uniform distribution is based. The genetic algorithm can be applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L₂norm of the difference between measured and modeled signals. The observed signals can be separated into a set of two signals reflected from the upper and lower boundaries of a sediment. The separation of signals and successive applications of the genetic algorithm optimization process reduce the search space, therefore improving the inversion results. Not only the marginal pdf but also the statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm. The examples applied here show that, for synthetic data with noise, it is possible to carry out an inversion for sedimentary layers using the proposed inversion method.

• Spatial Information Research
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• v.19 no.2
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• pp.29-36
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• 2011

This study performed quantitative assessment of the performance of adjustment models by a-priori analysis of the statistics of the surface parameter estimates against modeling factors. Lidar, airborne imagery, and SAR imagery have been used to acquire the earth surface elevation, where the shape properties of the surface need to be determined through neighboring observations around target location. In this study, parameters which are selected to be estimated are elevation, slope, second order coefficient. In this study, several factors which are needed to be specified to compose adjustment models are classified into three types: mathematical functions, kernel sizes, and weighting types. Accordingly, a-priori standard deviations of the parameters are computed for varying adjustment models. Then their corresponding confidence regions for both the standard deviation of the estimate and the estimate itself are calculated in association with probability distributions. Thereafter, the resulting confidence regions are compared to each other against the factors constituting the adjustment models and the quantitative performance of adjustment models are ascertained.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.540-547
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• 2004

Since speech enhancement algorithms based on Kalman/Wiener filter require a priori knowledge of the noise and have focused on the minimization of the variance of the estimation error between clean and estimated speech signal, small estimation error on the noise statistics may lead to large estimation error. However, H/sub ∞/ filter does not require any assumptions and a priori knowledge of the noise statistics, but searches the best estimated signal among the entire estimated signal by applying least upper bound, consequently it is more robust to the variation of noise statistics than Kalman/Wiener filter. In this paper, we Propose a speech enhancement method using HMM and multi H/sub ∞/ filters. First, HMM parameters are estimated with the training data. Secondly, speech is filtered with multiple number of H/sub ∞/ filters. Finally, the estimation of clean speech is obtained from the sum of the weighted filtered outputs. Experimental results shows about 1dB∼2dB SNR improvement with a slight increment of computation compared with the Kalman filter method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.210-212
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• 1996

Random drift rate (i.e., random drift in angle rate) of a gyro represents the major error source of inertial navigation systems that are required to operate over long time intervals. It is uncorrectable and leads to an increase in the error with the passage of time. In this paper a technique is presented for analyzing random process from experimental data and the results are presented. The problem of estimating the a priori statistics of a random process is considered using time averages of experimental data. Time averages are calculated and used in the optimal data-processing techniques to determine the statistics of the random process. Therefore the contribution each component to the gyro drift process can be quantitatively measured by its statistics. The above techniques will be applied to actual gyro drift rate data with satisfactory results.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.131-143
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• 1994

Under the asymmetric losses (entropy loss and Stein loss), we find the classes of Bayes and empiricla Bayes estimates for estimating the Poisson means when the distributin of means are believed a priori. Following the idea of Efron and Morris (1973), we have a computer simulation to compute a relative savings loss of proposed estimates as compared to the classical estimates.