• Title/Summary/Keyword: 사후확률

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Multi-focus Image Fusion Technique Based on Parzen-windows Estimates (Parzen 윈도우 추정에 기반한 다중 초점 이미지 융합 기법)

  • Atole, Ronnel R.;Park, Daechul
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.4
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    • pp.75-88
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    • 2008
  • This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

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A study on MERS-CoV outbreak in Korea using Bayesian negative binomial branching processes (베이지안 음이항 분기과정을 이용한 한국 메르스 발생 연구)

  • Park, Yuha;Choi, Ilsu
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.153-161
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    • 2017
  • Branching processes which is used for epidemic dispersion as stochastic process model have advantages to estimate parameters by real data. We have to estimate both mean and dispersion parameter in order to use the negative binomial distribution as an offspring distribution on branching processes. In existing studies on biology and epidemiology, it is estimated using maximum-likelihood methods. However, for most of epidemic data, it is hard to get the best precision of maximum-likelihood estimator. We suggest a Bayesian inference that have good properties of statistics for small-sample. After estimating dispersion parameter we modelled the posterior distribution for 2015 Korea MERS cases. As the result, we found that the estimated dispersion parameter is relatively stable no matter how we assume prior distribution. We also computed extinction probabilities on branching processes using estimated dispersion parameters.

A Development of Summer Seasonal Rainfall and Extreme Rainfall Outlook Using Bayesian Beta Model and Climate Information (기상인자 및 Bayesian Beta 모형을 이용한 여름철 계절강수량 및 지속시간별 극치 강수량 전망 기법 개발)

  • Kim, Yong-Tak;Lee, Moon-Seob;Chae, Byung-Soo;Kwon, Hyun-Han
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.5
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    • pp.655-669
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    • 2018
  • In this study, we developed a hybrid forecasting model based on a four-parameter distribution which allows a simultaneous season-ahead forecasting for both seasonal rainfall and sub-daily rainfall in Han-River and Geum-River basins. The proposed model is mainly utilized a set of time-varying predictors and the associated model parameters were estimated within a Bayesian nonstationary rainfall frequency framework. The hybrid forecasting model was validated through an cross-validatory experiment using the recent rainfall events during 2014~2017 in both basins. The seasonal precipitation results showed a good agreement with the observations, which is about 86.3% and 98.9% in Han-River basin and Geum-River basin, respectively. Similarly, for the extreme rainfalls at sub-daily scale, the results showed a good correspondence between the observed and simulated rainfalls with a range of 65.9~99.7%. Therefore, it can be concluded that the proposed model could be used to better consider climate variability at multiple time scales.

Uncertainty Assessment of Single Event Rainfall-Runoff Model Using Bayesian Model (Bayesian 모형을 이용한 단일사상 강우-유출 모형의 불확실성 분석)

  • Kwon, Hyun-Han;Kim, Jang-Gyeong;Lee, Jong-Seok;Na, Bong-Kil
    • Journal of Korea Water Resources Association
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    • v.45 no.5
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    • pp.505-516
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    • 2012
  • The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.

A Study on Modified Linear Prediction Method to Improve Target Estimation (목표물 추정 향상을 위한 수정 선형 예측방법에 대한 연구)

  • Lee, Kwan-Hyeong;Joo, Jong-Hyuk
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.4
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    • pp.337-342
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    • 2016
  • In this paper, we studied a modified linear prediction method to estimate target signal correctly. Linear prediction method estimate direction-of-arrival to linear combination for any antenna element and other antenna elements. Modified linear prediction used optimal weight and posterior probability method. Through simulation, we are comparative analysis about the performance of proposed, bartlett and MUSIC method. From simulation, Bartlett and MUSIC method was estimation 3 targets signal, and proposed method estimated 4 targets. We showed the superior performance of the proposed algorithm relative to the classical method in order to estimate of target signals.

A Study on Predicting Bankruptcy Discriminant Model for Small-Sized Venture Firms using Technology Evaluation Data (기술력평가 자료를 이용한 중소벤처기업 파산예측 판별모형에 관한 연구)

  • Sung Oong-Hyun
    • Journal of Korea Technology Innovation Society
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    • v.9 no.2
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    • pp.304-324
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    • 2006
  • There were considerable researches by finance people trying to find out business ratios as predictors of corporate bankruptcy. However, such financial ratios usually lack theoretical justification to predict bankruptcy for technology-oriented small sized venture firms. This study proposes a bankruptcy predictive discriminant model using technology evaluation data instead of financial data, evaluates the model fit by the correct classification rate, cross-validation method and M-P-P method. The results indicate that linear discriminant model was found to be more appropriate model than the logistic discriminant model and 69% of original grouped data were correctly classified while 67% of future data were expected to be classified correctly.

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Image Adaptive Block DCT-Based Perceptual Digital Watermarking (영상 특성에 적응적인 블록 DCT 기반 지각적 디지털 워터마킹)

  • 최윤희;최태선
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.6
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    • pp.221-229
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    • 2004
  • We present new digital watermarking scheme that embeds a watermark according to the characteristics of the image or video. The scheme is compatible with established image compression standard. We define a weighting function using a parent-child structure of the DCT coefficients in a block to embed a maximum watermark. The spatio-frequency localization of the DCT coefficients can be achieved with this structure. In the detection stage, we present an optimum a posteriori threshold with a given false detection error probability based on the statistical analysis. Simulation results show that the proposed algorithm is efficient and robust against various signal processing techniques. Especially, they are robust against widely used coding standards, such as JPEG and MPEG.

The Structure and Performance of Turbo decoder using Sliding-window method (슬라이딩 윈도우 방식의 터보 복호화기의 구조 및 성능)

  • 심병효;구창설;이봉운
    • Journal of the Korea Institute of Military Science and Technology
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    • v.3 no.1
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    • pp.116-126
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    • 2000
  • Turbo codes are the most exciting and potentially important development in coding theory in recent years. They were introduced in 1993 by Berrou, Glavieux and $Thitimajshima,({(1)}$ and claimed to achieve near Shannon-limit error correction performance with relatively simple component codes and large interleavers. A required Eb/N0 of 0.7㏈ was reported for BER of $10^{-5}$ and code rate of $l/2.^{(1)}$ However, to implement the turbo code system, there are various important details that are necessary to reproduce these results such as AGC gain control, optimal wordlength determination, and metric rescaling. Further, the memory required to implement MAP-based turbo decoder is relatively considerable. In this paper, we confirmed the accuracy of these claims by computer simulation considering these points, and presented a optimal wordlength for Turbo code design. First, based on the analysis and simulation of the turbo decoder, we determined an optimal wordlength of Turbo decoder. Second, we suggested the MAP decoding algorithm based on sliding-window method which reduces the system memory significantly. By computer simulation, we could demonstrate that the suggested fixed-point Turbo decoder operates well with negligible performance loss.

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A Post-Examination of Forecasting Surveys for the 16th General Election (제 16대 국회의원 선거의 예측조사에 대한 사후적 검증)

  • 홍내리;허명희
    • Proceedings of the Korean Association for Survey Research Conference
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    • 2001.04a
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    • pp.1.2-35
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    • 2001
  • On the election day of the 16th Korea national Assembly, nationwide TV stations such as KBS, SBS and MBC broadcasted election forecasting based on telephone surveys and exit polls. The result turned out to be significantly wrong, undermining general audience's confidence on the 'ientific'surveys. The purpose of this study consists of the followings. I) What form of telephone surveys and exit polls were adopted by survey institutions in real field\ulcorner ii) What were the problems\ulcorner iii) What can we do to make it straight\ulcorner Major findings of the study include the ignorance of call-back rules in telephone survey and the inadequate number of sampled election posts to make satisfactory forecasting. It is pointed out that it is necessary to amend election laws related to election opinion polls to make a substantial progress.

A Unified Bayesian Tikhonov Regularization Method for Image Restoration (영상 복원을 위한 통합 베이즈 티코노프 정규화 방법)

  • Yoo, Jae-Hung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.11
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    • pp.1129-1134
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    • 2016
  • This paper suggests a new method of finding regularization parameter for image restoration problems. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, unified Bayesian interpretation of Tikhonov regularization is introduced and applied to the image restoration problems. The relationship between Tikhonov regularization parameter and Bayesian hyper-parameters is established. Update formular for the regularization parameter using both maximum a posteriori(: MAP) and evidence frameworks is suggested. Experimental results show the effectiveness of the proposed method.