• Title/Summary/Keyword: 이상치 추정

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"Pansori" Joint Assumption using Neural Network (인공신경망을 이용한 판소리 마디추정)

  • Park, Keunho;Seo, Kyoung-suk;Lee, Joonwhoan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.11a
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    • pp.975-977
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    • 2014
  • 본 논문에서는 판소리 자동채보에 중요한 요소인 '합'과 '궁'의 위치 즉 마디를 인공신경망과 히스토그램을 이용하여 추정한다. 기존의 합과 궁을 추정하는 방법으로는 NCC(Normalized Cross Correlation)를 이용한 대표치 추정 윈도우와 칼만 필터를 이용하였다. 하지만 대표치 추정 윈도우를 구성하는 과정에서 단순히 15개의 특징벡터 각각의 평균을 이용하기 때문에 분별력이 떨어지고, 마디위치를 보정하는 과정에서 칼만 필터를 사용하면 전체음원이 길이가 짧을 경우 오차가 발생할 가능성이 크다. 본 논문에서 제안한 마디 추정 알고리즘은 장단별로 최대 90%이상의 정확도로 마디를 추정할 수 있다.

Real-time Decision of G/R Ratio using the Dual Kalman Filter (Dual Kalman Filter를 이용한 G/R 비의 실시간 결정)

  • Yoo, Chul-Sang;Kim, Jung-Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2011.05a
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    • pp.353-356
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    • 2011
  • 본 연구에서는 G/R 비의 실시간 결정을 목적으로 Dual Kalman Filter를 이용하였다. Dual Kalman Filter 는 이중추정(dual estimation)을 기반으로 하는 자료동화기법으로 기존 Kalman Filter와 상이한 상태-공간 모형으로 구성된다. 이에 Dual Kalman Filter와 기존 Kalman Filter의 적용성능을 비교 검토하였으며, 다양한 비교를 위하여 강우의 임계치와 누적시간의 고려여부에 따른 결과를 추가적으로 검토하였다. 두 기법의 적용성능 비교결과 Dual Kalman Filter가 우수한 것으로 나타났다. 이는 Dual Kalman Filter 기법이 G/R 비의 큰 변동성과 이상치를 효과적으로 필터링하고, 시계열 모형의 매개변수를 실시간으로 갱신하여 정확한 예측치를 추정하였기 때문인 것으로 판단된다.

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K-F기법으로 실업자 수의 소지역추정 - 경제활동인구조사를 중심으로 -

  • Yang, Yeong-Chun;Lee, Sang-Eun;Sin, Min-Ung
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.11a
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    • pp.305-309
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    • 2002
  • 소지역에서 직접(direct) 시계열추정을 할 수 있다면, 소지역들 추정에서 최적선형 불편예측량(BLUP)을 일반화 시킬 수 있다. 특히 조사에서 얻어지는 관측 값의 오차가 시간상으로 상관관계가 있다면 Kalman-Filter(K-F)기법이 사용 될 수 있다. 이 연구는 소지역의 실업자 수 추정에서 K-F기법으로 경제활동인구수를 이용하여 현 시점의 소지역 실업자 수를 예측함수(BLUP)를 통해 추정하였다. 그리고 단순 회귀분석 추정치와 비교하였다.

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A Study on tractive effort control for Railway Vehicle (철도차량의 최대견인력 제어를 위한 연구)

  • Chung, Choon-Byeong;Kim, Dae-Gun;Hahm, Nyun-Gun;Lee, Sang-Chip;Jeon, Kee-Young;Lee, Hun-Gu;Han, Kjyung-Hee
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2005.05a
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    • pp.265-269
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    • 2005
  • 본 논문에서는 최대 견인력 제어를 위해서 최소 차원 부하 토크 외란 관측기를 이용하여 점착력 계수를 추정하고 추정한 점착력 계수의 미분치를 PI 토크 제어하는 Anti-slip제어를 제안한다. 최소차원 부하 토크 외란 관측기는 회전자의 위치 정보와 토크 전류의 정보를 이용하여 부하 외란토크를 추정하고, 부하 외란 토크에 철도차량 상수를 이용하여 점착력 계수를 추정한다. 또한 부하토크외란 관측기는 구조가 간단하며, 시스템의 외란 및 각종 제어이득, 시스템의 상수 변화에 대해서도 견실한 견인력 제어 특성을 가지고 있다. 이와 같은 시스템의 모델링과 전동기 토크에 대한 회전자의 위치 정보를 이용하여 최소차원 부하 토크 외란 관측기의 상태변수인 점착력 계수를 추정하고, 추정한 점착력 계수의 미분치를 PI토크 Anti-Slip제어하여, 최대 견인력 제어가 되도록 하였다.

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Fast robust variable selection using VIF regression in large datasets (대형 데이터에서 VIF회귀를 이용한 신속 강건 변수선택법)

  • Seo, Han Son
    • The Korean Journal of Applied Statistics
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    • v.31 no.4
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    • pp.463-473
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    • 2018
  • Variable selection algorithms for linear regression models of large data are considered. Many algorithms are proposed focusing on the speed and the robustness of algorithms. Among them variance inflation factor (VIF) regression is fast and accurate due to the use of a streamwise regression approach. But a VIF regression is susceptible to outliers because it estimates a model by a least-square method. A robust criterion using a weighted estimator has been proposed for the robustness of algorithm; in addition, a robust VIF regression has also been proposed for the same purpose. In this article a fast and robust variable selection method is suggested via a VIF regression with detecting and removing potential outliers. A simulation study and an analysis of a dataset are conducted to compare the suggested method with other methods.

Usefulness and Limitations of Extreme Value Theory VAR model : The Korean Stock Market (극한치이론을 이용한 VAR 추정치의 유용성과 한계 - 우리나라 주식시장을 중심으로 -)

  • Kim, Kyu-Hyong;Lee, Joon-Haeng
    • The Korean Journal of Financial Management
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    • v.22 no.1
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    • pp.119-146
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    • 2005
  • This study applies extreme value theory to get extreme value-VAR for Korean Stock market and showed the usefulness of the approach. Block maxima model and POT model were used as extreme value models and tested which model was more appropriate through back testing. It was shown that the block maxima model was unstable as the variation of the estimate was very large depending on the confidence level and the magnitude of the estimates depended largely on the block size. This shows that block maxima model was not appropriate for Korean Stock market. On the other hand POT model was relatively stable even though extreme value VAR depended on the selection of the critical value. Back test also showed VAR showed a better result than delta VAR above 97.5% confidence level. POT model performs better the higher the confidence level, which suggests that POT model is useful as a risk management tool especially for VAR estimates with a confidence level higher than 99%. This study picks up the right tail and left tail of the return distribution and estimates the EVT-VAR for each, which reflects the asymmetry of the return distribution of the Korean Stock market.

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Gravitational deflection analysis for the shielded slot plate with many tiny structures (미세 구조물이 성형된 쉴드슬롯판의 자중 처짐 해석)

  • Lee S.W.;Shim U.T.;Lee K.S.;Woo D.U.;Kim J.H.
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.7 no.3
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    • pp.291-297
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    • 2006
  • In this study, the equivalent physical properties of the shielded slot plate having a lot of very tiny bridge shape structures on its plane were determined by tensile tests and structural analyses. With those results, numerical analyses for the deflection profile by gravity effect were carried out to compare with experimental results. The two results were shown coincident very well so that the estimated equivalent physical properties were verified enough for further studies such as curvature reduction for the shielded slot plate.

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Differences Between Analyzed and Estimated Sodium Contents of Food Composition Table or Food Exchange List (나트륨 실측치와 식품교환표 및 식품성분표를 이용한 추정치의 비교)

  • Kwon, Yong-Ju;Rhee, Moo-Yong;Kim, Jee-Young;Kwon, Kwang-Il;Kim, So-Jin;Shin, Hee-Jun;Park, Seong-Soo;Lee, Eun-Ju;Park, Hye-Kyung;Park, Yong-Soon
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.39 no.4
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    • pp.535-541
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    • 2010
  • Excessive intake of sodium is known as a risk factor for hypertension, and Korean adults consume sodium 3 times higher than Dietary Reference Intakes (DRIs). The purpose of this study was to evaluate the difference on sodium content between analyzed and estimated by food composition table and food exchange list. Seven days of low salt diet and seven days of high salt diet were prepared, and sodium contents were estimated by food composition table and food exchange list and measured by atomic absorption spectrophotometer. Sodium contents of diet per day estimated by food exchange list significantly differed from analyzed content, but those estimated by food composition table were not. However, when absolute differences from analyzed content were compared by dishes in the low and high salt diet periods, there were significant differences among estimated sodium content by food composition table and food exchange list and analyzed sodium content. The discrepancy between those results was due to that absolute value was used to compare sodium contents of dishes but not to compare sodium contents of days. In addition, main dish, side dish, and soup were significantly different among estimated sodium content by food composition table and food exchange list and analyzed sodium content. Actual sodium contents of Jap-Chae Deop-Bap and Roasted chicken with oyster sauce differed to a great extent from estimated contents by food exchange list and food composition table. In conclusion, actual sodium contents of Korean dishes were significantly different from those estimated by food composition table and food exchange list, and thus these differences in salt content should be considered on planning of low-salt menu for hypertensive patients.

Robust Response Transformation Using Outlier Detection in Regression Model (회귀모형에서 이상치 검색을 이용한 로버스트 변수변환방법)

  • Seo, Han-Son;Lee, Ga-Yoen;Yoon, Min
    • The Korean Journal of Applied Statistics
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    • v.25 no.1
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    • pp.205-213
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    • 2012
  • Transforming response variable is a general tool to adapt data to a linear regression model. However, it is well known that response transformations in linear regression are very sensitive to one or a few outliers. Many methods have been suggested to develop transformations that will not be influenced by potential outliers. Recently Cheng (2005) suggested to using a trimmed likelihood estimator based on the idea of the least trimmed squares estimator(LTS). However, the method requires presetting the number of outliers and needs many computations. A new method is proposed, that can solve the problems addressed and improve the robustness of the estimates. The method uses a stepwise procedure, suggested by Hadi and Simonoff (1993), to detect outliers that determine response transformations.

An Adaptive Time Delay Estimation Method Based on Canonical Correlation Analysis (정준형 상관 분석을 이용한 적응 시간 지연 추정에 관한 연구)

  • Lim, Jun-Seok;Hong, Wooyoung
    • The Journal of the Acoustical Society of Korea
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    • v.32 no.6
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    • pp.548-555
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    • 2013
  • The localization of sources has a numerous number of applications. To estimate the position of sources, the relative delay between two or more received signals for the direct signal must be determined. Although the generalized cross-correlation method is the most popular technique, an approach based on eigenvalue decomposition (EVD) is also popular one, which utilizes an eigenvector of the minimum eigenvalue. The performance of the eigenvalue decomposition (EVD) based method degrades in the low SNR and the correlated environments, because it is difficult to select a single eigenvector for the minimum eigenvalue. In this paper, we propose a new adaptive algorithm based on Canonical Correlation Analysis (CCA) in order to extend the operation range to the lower SNR and the correlation environments. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue in the generalized eigenvalue decomposition (GEVD). The estimated eigenvector contains all the information that we need for time delay estimation. We have performed simulations with uncorrelated and correlated noise for several SNRs, showing that the CCA based algorithm can estimate the time delays more accurately than the adaptive EVD algorithm.