• Title/Summary/Keyword: maximum likelihood rule

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A Statistical Model-Based Voice Activity Detection Employing the Conditional MAP Criterion with Spectral Deviation (조건 사후 최대 확률과 음성 스펙트럼 변이 조건을 이용한 통계적 모델 기반의 음성 검출기)

  • Kim, Sang-Kyun;Chang, Joon-Hyuk
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.6
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    • pp.324-329
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    • 2011
  • In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the conditional maximum a posteriori (CMAP) with deviation. In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the speech activity decisions and spectral deviation in the pervious frame. Experimental results show that the proposed approach yields better results compared to the CMAP-based VAD using the LR test.

COMPOUNDED METHOD FOR LAND COVERING CLASSIFICATION BASED ON MULTI-RESOLUTION SATELLITE DATA

  • HE WENJU;QIN HUA;SUN WEIDONG
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.116-119
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    • 2005
  • As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.

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Accelerated Life Testings for System based on a Bivariate Exponential Model

  • Park, Byung-Gu;Yoon, Sang-Chul
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.423-432
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    • 1999
  • Accelerated life testing of product is commonly used to reduced test time and costs. In this papers is considered when the product is a two component system with lifetimes following the bivariate exponential distribution of Sarkar(1987) using inverse power rule model. Also we derived the maximum likelihood estimators of parameters for asymptotic normality. We compare the mean square error of the proposed estimator for the life distribution under use conditions stree through Monte Carlo simulation.

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Objective Bayesian inference based on upper record values from Rayleigh distribution

  • Seo, Jung In;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.411-430
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    • 2018
  • The Bayesian approach is a suitable alternative in constructing appropriate models for observed record values because the number of these values is small. This paper provides an objective Bayesian analysis method for upper record values arising from the Rayleigh distribution. For the objective Bayesian analysis, the Fisher information matrix for unknown parameters is derived in terms of the second derivative of the log-likelihood function by using Leibniz's rule; subsequently, objective priors are provided, resulting in proper posterior distributions. We examine if these priors are the PMPs. In a simulation study, inference results under the provided priors are compared through Monte Carlo simulations. Through real data analysis, we reveal a limitation of the appropriate confidence interval based on the maximum likelihood estimator for the scale parameter and evaluate the models under the provided priors.

Estimation of Maximal Tolerated Dose in Sequential Phase I Clinical Trials

  • Park, In-Hye;Song, Hae-Hiang
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.543-564
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    • 1999
  • The principal aim of a sequential phase I clinical trial in which the toxicity reponses of a group of patient(s) determine the dose level of the next patient(s) group is to estimate the maximal tolerated dose(MTD) of a new drug, In this paper we compared with a simulation study the performance of the MTD estimates that are determined by a stopping rule in a design and also those that are determined by analyzing the data after a clinical trial is terminated. To the latter belong the mean median mode and maximum likelihood estimates. For the Standard Methods the stopping rule MTD is quite inefficient but the median MTD has a best efficiency and is robust with respect to the three different toxicity curves. The problem of non-convergence of MLE MTD is severe. A more improved MTD estimate is produced by combining the advantages of the various MTD estimates and its efficiency is better than the single median MTD estimate especially for the toxicity curve of an unlucky choice of dose levels. The simulation results suggest that simple types of phase I designs can be combined with relatively standard analytic techniques to provide a more efficient MTD estimate.

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A Study on the Poorly-posed Problems in the Discriminant Analysis of Growth Curve Model

  • Shim, Kyu-Bark
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.87-100
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    • 2002
  • Poorly-posed problems in the balanced discriminant analysis was considered. We restrict consideration to the case of observations and the number of variables are the same and small. When these problems exist, we do not use a maximum likelihood estimates(MLE) to estimate covariance matrices. Instead of MLE, an alternative estimate for the covariance matrices are proposed. This alternative method make good use of two regularization parameters, $\lambda$} and $\gamma$. A new test rule for the discriminant function is suggested and examined via limited hut informative simulation study. From the simulation study, it is shown that the suggested test rule gives better test result than other previously suggested method in terms of error rate criterion.

Evaluation of the Pi-SAR Data for Land Cover Discrimination

  • Amarsaikhan, D.;Sato, M.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1087-1089
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    • 2003
  • The aim of this study is to evaluate the Pi-SAR data for land cover discrimination using a standard method. For this purpose, the original polarization and Pauli components of the Pi-SAR X-band and L-band data are used and the results are compared. As a method for the land cover discrimination, the traditional method of statistical maximum likelihood decision rule is selected. To increase the accuracy of the classification result, different spatial thresholds based on local knowledge are determined and used for the actual classification process. Moreover, to reduce the speckle noise and increase the spatial homogeneity of different classes of objects, a speckle suppression filter is applied to the original Pi-SAR data before applying the classification decision rule. Overall, the research indicated that the original Pi-SAR polarization components can be successfully used for separation of different land cover types without taking taking special polarization transformations.

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A Study on the Estimation of Optimal Probability Distribution Function for Seafarers' Behavior Error (선원 행동오류에 대한 최적 확률분포함수 추정에 관한 연구)

  • Park, Deuk-Jin;Yang, Hyeong-Seon;Yim, Jeong-Bin
    • Journal of Navigation and Port Research
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    • v.43 no.1
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    • pp.1-8
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    • 2019
  • Identifying behavioral errors of seafarers that have led to marine accidents is a basis for research into prevention or mitigation of marine accidents. The purpose of this study is to estimate the optimal probability distribution function needed to model behavioral errors of crew members into three behaviors (i.e., Skill-, Rule-, Knowledge-based). Through use of behavioral data obtained from previous accidents, we estimated the optimal probability distribution function for the three behavioral errors and verified the significance between the probability values derived from the probability distribution function. Maximum Likelihood Estimation (MLE) was applied to the probability distribution function estimation and variance analysis (ANOVA) used for the significance test. The obtained experimental results show that the probability distribution function with the smallest error can be estimated for each of the three behavioral errors for eight types of marine accidents. The statistical significance of the three behavioral errors for eight types of marine accidents calculated using the probability distribution function was observed. In addition, behavioral errors were also found to significantly affect marine accidents. The results of this study can be applied to predicting marine accidents caused by behavioral errors.

New Decision Rules for UWB Synchronization (UWB 동기화를 위한 새로운 결정 법칙들)

  • Chong, Da-Hae;Lee, Young-Yoon;Ahn, Sang-Ho;Lee, Eui-Hyoung;Yoo, Seung-Hwan;Yoon, Seok-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.2C
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    • pp.192-199
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    • 2008
  • In ultra-wideband (UWB) systems, conventionally, the synchronization is to align time phases of a locally generated template and any of multipath components to within an allowable range. However, the synchronization with a low-power multipath component could incur significant performance degradation in receiver operation (e.g., detection) after the synchronization. On the other hand, the synchronization with a high-power multipath component can improve the performance in receiver operation after the synchronization. Generally, the first one among multipath components has the largest power. Thus, the synchronization with the first path component can make better performance than that with low-power component in receiver operation after the synchronization, Based on which, we first propose an optimal decision rule based on a maximum likelihood (ML) approach, and then, develope a simpler suboptimal decision rule for selecting the first path component. Simulation results show that the system has good demodulation performance, which uses new synchronization definition and the proposed decision rules have better performance than that of the conventional decision rule in UWB multipath channels. Between macroblocks in the previous and the current frame. On video samples with high motion and scene change cases, experimental results show that (1) the proposed algorithm adapts the encoded bitstream to limited channel capacity, while existing algorithms abruptly excess the limit bit rate; (2) the proposed algorithm improves picture quality with $0.4{\sim}0.9$dB in average.

Feature Extraction and Multisource Image Classification

  • Amarsaikhan, D.;Sato, M.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1084-1086
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    • 2003
  • The aim of this study is to assess the integrated use of different features extracted from spaceborne interferometric synthetic aperture radar (InSAR) data and optical data for land cover classification. Special attention is given to the discriminatory characteristics of the features derived from the multisource data sets. For the evaluation of the features , the statistical maximum likelihood decision rule and neural network classification are used and the results are compared. The performance of each method was evaluated by measuring the overall accuracy. In all cases, the performance of the first method was better than the performance of the latter one. Overall, the research indicated that multisource data sets containing different information about backscattering and reflecting properties of the selected classes of objects can significantly improve the classification of land cover types.

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