• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.83-91
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• 2016

Music-similarity computation is crucial in developing music information retrieval systems for browsing and classification. This paper overviews the recently-proposed centroid-model based music retrieval method and applies the distributional similarity measures to the model for retrieval-performance evaluation. Probabilistic distance measures (also called divergence) compute the distance between two probability distributions in a certain sense. In this paper, we consider the alpha divergence in computing distance between two centroid models for music retrieval. The alpha divergence includes the widely-used Kullback-Leibler divergence and Bhattacharyya distance depending on the values of alpha. Experiments were conducted on both genre and singer datasets. We compare the music-retrieval performance of the distributional similarity with that of the vector distances. The experimental results show that the alpha divergence improves the performance of the centroid-model based music retrieval.

• The Journal of the Acoustical Society of Korea
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• v.29 no.3
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• pp.216-221
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• 2010

In this paper, we propose speaker verification method using Support Vector Machine (SVM) kernel with Gaussian Mixture Model (GMM)-supervector based on the Mahalanobis distance. The proposed GMM-supervector SVM kernel method is combined GMM with SVM. The GMM-supervectors are generated by GMM parameters of speaker and other speaker utterances. A speaker verification threshold of GMM-supervectors is decided by SVM kernel based on Mahalanobis distance to improve speaker verification accuracy. The experimental results for text-independent speaker verification using 20 speakers demonstrates the performance of the proposed method compared to GMM, SVM, GMM-supervector SVM kernel based on Kullback-Leibler (KL) divergence, and GMM-supervector SVM kernel based on Bhattacharyya distance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.167-176
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• 2005

This paper describes how the state tying model based on the decision tree which is one of Acoustic models used for speech recognition optimizes the model by reducing the number of mixture Gaussians of the output probability distribution. The state tying modeling uses a finite set of questions which is possible to include the phonological knowledge and the likelihood based decision criteria. And the recognition rate can be improved by increasing the number of mixture Gaussians of the output probability distribution. In this paper, we'll reduce the number of mixture Gaussians at the highest point of recognition rate by clustering the Gaussians. Bhattacharyya and Euclidean method will be used for the distance measure needed when clustering. And after calculating the mean and variance between the pair of lowest distance, the new Gaussians are created. The parameters for the new Gaussians are derived from the parameters of the Gaussians from which it is born. Experiments have been performed using the STOCKNAME (1,680) databases. And the test results show that the proposed method using Bhattacharyya distance measure maintains their recognition rate at $97.2\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. And the method using Euclidean distance measure shows that it maintains the recognition rate at $96.9\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. Then the methods can optimize the state tying model.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.361-377
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• 2005

A mathematical model dealing with a prey-predator system with disease in the prey is considered. The functional response of the predator is governed by a Hoilling type-2 function. Mathematical analysis of the model regarding stability and persistence has been performed. The effect of delay and diffusion on the above system is studied. The role of diffusivity on stability and persistence criteria of the system has also been discussed.

• Journal of the Korean Chemical Society
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• v.56 no.1
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• pp.164-168
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• 2012

• Journal of the Korean Statistical Society
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• v.12 no.1
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• pp.1-9
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• 1983

A stress-strength model is formulated for s out of k system of identical components. We consider the estimation of system reliability from survival count data from a Bayesian viewpoint. We assume a quadratic loss and a Dirichlet prior distribution. It is shown that a Bayes sequential procedure can be established. The Bayes estimator is compared with the UMVUE obtained by Bhattacharyya and with an estimator based on Mann-Whitney statistic.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.71-80
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• 2000

본 논문에서는 이변량 분포함수의 위치모수에 대한 교대위치이동 대립가설에 대한 비모수적 검정법을 제안하였다. 소표본의 경우 실제 자료에 대해 순열원리에 기초한 근사적 검정법을 제시하였다. 모의실험을 통하여 Bhattacharyya와 Johnson(1970)의 층계순위(layer ranks)에 기초한 검정법과 검정력을 비교하였다.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.293-303
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• 1999

When test outcomes of units are dichotomous and he infection rate is small group testing is more efficient that noe-to-one testing in estimating the true p and classifying units as infected or not. In this paper two-sided hypothesis testing and confidence intervals are derived based on the UMP(uniformly most powerful) unbiased test. The UMP unbiased approach is compared with Thompson's and Bhattacharyya et al.'s approaches by computing the length of confidence intervals and capture probabilities and shown to have a number of desirable properties. Unequal allocation one of advantages of the proposed approach is also mentioned.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.317-325
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• 1997

Group testing is an efficient method to classify units from a population as infected or non-infected and useful in estimating the infection rate when the population infection rate is small. Upper bounds are the focus of interest in group testing, but has not been studied extensively. In this paper, the upper bound derived from the uniformly most powerful test is proposed and compared with the classical approachers, Thompson's and Bhattacharyya et al.'s methods.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.467-470
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• 1994

In this paper, we develop two sufficient conditions for Schur stability of convex combinations of discrete time polynomials. We give conditions under which Schur stability of the extremes implies Schur stability of the entire convex combination. These results are based on Bhattacharyya's result(1991), the AHMC theory in Barmish and Kang's paper (1993) and the bilinear transformation. Important applications of the results involves robust Schur stability of a feedback system having degenerate interval plants in an extreme point context.