• Title/Summary/Keyword: probability-based

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An Improved Speech Absence Probability Estimation based on Environmental Noise Classification (환경잡음분류 기반의 향상된 음성부재확률 추정)

  • Son, Young-Ho;Park, Yun-Sik;An, Hong-Sub;Lee, Sang-Min
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.7
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    • pp.383-389
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    • 2011
  • In this paper, we propose a improved speech absence probability estimation algorithm by applying environmental noise classification for speech enhancement. The previous speech absence probability required to seek a priori probability of speech absence was derived by applying microphone input signal and the noise signal based on the estimated value of a posteriori SNR threshold. In this paper, the proposed algorithm estimates the speech absence probability using noise classification algorithm which is based on Gaussian mixture model in order to apply the optimal parameter each noise types, unlike the conventional fixed threshold and smoothing parameter. Performance of the proposed enhancement algorithm is evaluated by ITU-T P.862 PESQ (perceptual evaluation of speech quality) and composite measure under various noise environments. It is verified that the proposed algorithm yields better results compared to the conventional speech absence probability estimation algorithm.

Monte Carlo Estimation of Multivariate Normal Probabilities

  • Oh, Man-Suk;Kim, Seung-Whan
    • Journal of the Korean Statistical Society
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    • v.28 no.4
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    • pp.443-455
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    • 1999
  • A simulation-based approach to estimating the probability of an arbitrary region under a multivariate normal distribution is developed. In specific, the probability is expressed as the ratio of the unrestricted and the restricted multivariate normal density functions, where the restriction is given by the region whose probability is of interest. The density function of the restricted distribution is then estimated by using a sample generated from the Gibbs sampling algorithm.

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Determination of threshold values for color image segmentation (색도 영상분할을 위한 문턱치 결정방법)

  • 이병욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.4
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    • pp.869-875
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    • 1996
  • This paper investigates a method for dtermining a threshold value based on the probability distribution function for color image segmentation. Principal components of normalized color is nalyzed and found that there are effective color transforms for outdoor scents. We esplain the functional relationship of the treshold and the probability of a regiona detection, asuming bivarate Gaussian probability density function. Experimental results show that the probability of detection is proportional to the segmented area.

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Ontology based Educational Systems using Discrete Probability Techniques (이산 확률 기법을 이용한 온톨로지 기반 교육 시스템)

  • Lee, Yoon-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.1 s.45
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    • pp.17-24
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    • 2007
  • Critical practicality problems are cause to search the presentation and contents according to user request and purpose in previous internet system. Recently, there are a lot of researches about dynamic adaptable ontology based system. We designed ontology based educational system which uses discrete probability and user profile. This system provided advanced usability of contents by ontology and dynamic adaptive model based on discrete probability distribution function and user profile in ontology educational systems. This models represents application domain to weighted direction graph of dynamic adaptive objects and modeling user actions using dynamically approach method structured on discrete probability function. Proposed probability analysis can use that presenting potential attribute to user actions that are tracing search actions of user in ontology structure. This approach methods can allocate dynamically appropriate profiles to user.

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A Study on Background Speaker Selection Method in Speaker Verification System (화자인증 시스템에서 선정 방법에 관한 연구)

  • Choi, Hong-Sub
    • Speech Sciences
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    • v.9 no.2
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    • pp.135-146
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    • 2002
  • Generally a speaker verification system improves its system recognition ratio by regularizing log likelihood ratio, using a speaker model and its background speaker model that are required to be verified. The speaker-based cohort method is one of the methods that are widely used for selecting background speaker model. Recently, Gaussian-based cohort model has been suggested as a virtually synthesized cohort model, and unlike a speaker-based model, this is the method that chooses only the probability distributions close to basic speaker's probability distribution among the several neighboring speakers' probability distributions and thereby synthesizes a new virtual speaker model. It shows more excellent results than the existing speaker-based method. This study compared the existing speaker-based background speaker models and virtual speaker models and then constructed new virtual background speaker model groups which combined them in a certain ratio. For this, this study constructed a speaker verification system that uses GMM (Gaussin Mixture Model), and found that the suggested method of selecting virtual background speaker model shows more improved performance.

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A CUSUM Chart Based on Log Probability Ratio Statistic

  • Park, Chang-Soon;Kim, Byung-Chun
    • Journal of the Korean Statistical Society
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    • v.19 no.2
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    • pp.160-170
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    • 1990
  • A new approximation method is proposed for the ARL of CUSUM chart which is based on the log probability ratio statistic. This method uses the condition of before-stopping time to derive the expectation of excess over boundaries. The proposed method is compared to some other approximation methods in normal and exponential cases.

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Optimization-based method for structural damage detection with consideration of uncertainties- a comparative study

  • Ghiasi, Ramin;Ghasemi, Mohammad Reza
    • Smart Structures and Systems
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    • v.22 no.5
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    • pp.561-574
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    • 2018
  • In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

A Study on Properties of Crude Oil Based Derivative Linked Security (유가 연계 파생결합증권의 특성에 대한 연구)

  • Sohn, Kyoung-Woo;Chung, Ji-Yeong
    • Asia-Pacific Journal of Business
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    • v.11 no.3
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    • pp.243-260
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    • 2020
  • Purpose - This paper aims to investigate the properties of crude oil based derivative security (DLS) focusing on step-down type for comprehensive understanding of its risk. Design/methodology/approach - Kernel estimation is conducted to figure out statistical feature of the process of oil price. We simulate oil price paths based on kernel estimation results and derive probabilities of hitting the barrier and early redemption. Findings - The amount of issuance for crude oil based DLS is relatively low when base prices are below $40 while it is high when base prices are around $60 or $100, which is not consistent with kernel estimation results showing that oil futures prices tend to revert toward $46.14 and the mean-reverting speed is faster as oil price is lower. The analysis based on simulated oil price paths reveals that probability of early redemption is below 50% for DLS with high base prices and the ratio of the probability of early redemption to the probability of hitting barrier is remarkably low compared to the case for DLS with low base prices, as the chance of early redemption is deferred. Research implications or Originality - Empirical results imply that the level of the base price is a crucial factor of the risk for DLS, thus introducing a time-varying knock-in barrier, which is similar to adjust the base price, merits consideration to enhance protection for DLS investors.

A Study on Probability of Bit Error for Wavelet in 4-ary SWSK System (4-ary SWSK 시스템에서 웨이브릿에 대한 비트 에러 확률에 관한 연구)

  • Jeong, Tae-Il
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.1
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    • pp.57-62
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    • 2011
  • This paper presents a study on the performance analysis on probability of bit error for wavelet in 4-ary SWSK system. The formula for the bit error probability in 4-ary SWSK system was derived from the conventional method. This paper experimentally implements the probability of bit error for Daubechies, Biorthogonal, Coiflet and Symlet wavelet using the conventional formula of bit error probability. Additionally, the performance of bit error probability is analyzed for the period and the number of wavelet taps. Based on the results, we confirmed that the performance of Coiflet and Symlet wavelet for the probability of bit error is superior to the other wavelet, and their probability of bit error are similar.

Probabilistic Prediction of Stability of Ship by Risk Based Approach

  • Long, Zhan-Jun;Lee, Seung-Keon;Lee, Sung-Jong;Jeong, Jae-Hun
    • Journal of Navigation and Port Research
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    • v.33 no.4
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    • pp.255-261
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    • 2009
  • Prediction of the stability for ships is very complex in reality. In this paper, risk based approach is applied to predict the probability of capsize for a certified ship, which is effected by the forces of sea especially the wave loading Safety assessment and risk analysis process are also applied for the probabilistic prediction of stability for ships. The probability of shipsencountering different waves at sea is calculated by the existed statistics data and risk based models. Finally, ship capsizing probability is calculated according to single degree of freedom(SDF) rolling differential equation and basin erosion theory of nonlinear dynamics. Calculation results show that the survival probabilities of ship excited by the forces of the seas, especially in the beam seas status, can be predicted by the risk based method.