• 제목/요약/키워드: Probability Vector

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VQ의 코드북 생성을 위한 LBG 알고리즘의 개선에 관한 연구 (A Study on an Improved LBG Algorithm to Design the Code Book of VQ)

  • 김장한
    • 한국통신학회논문지
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    • 제25권1A호
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    • pp.48-55
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    • 2000
  • 본 논문에서는 모의 실험을 통하여, 데이터의 분포가 Gauss 분포, 균등 분포 등의 경우, 어느 한 구간이 다른 구간에 비하여 확률도 크고 구간내의 오차도 크다면 이는 최적 양자화가 아니다라는 가정을 하였다. 이 가정을 LBG 알고리즘에 추가하여 수정된 LBG 알고리즘을 만들고, 이 알고리즘의 성능을 측정하였다. 수정된 알고리즘에 의한 코드 북의 오차는 본래의 알고리즘에 비하여 오차의 크기도 감소하였고, 오차의 편차도 감소하였다.

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확률 및 통계이론 기반 태양광 발전 시스템의 동적 모델링에 관한 연구 (A Study on Dynamic Modeling of Photovoltaic Power Generator Systems using Probability and Statistics Theories)

  • 조현철
    • 전기학회논문지
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    • 제61권7호
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    • pp.1007-1013
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    • 2012
  • Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

AFFINE MANIFOLD WITH MEASURE PRESERVING PROJECTIVE HOLONOMY GROUP

  • Park, Yeong-Su
    • 대한수학회보
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    • 제38권1호
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    • pp.157-161
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    • 2001
  • In this paper, we prove that an affine manifold M is finitely covered by a manifold $\overline{M}$ where $\overline{M}$ is radiant or the tangent bundle of $\overline{M}$ has a conformally flat vector subbundle of the projective holonomy group of M admits an invariant probability Borel measure. This implies that$x^M$is zero.

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Karhunen-loeve 변환과 분류 벡터 양자화에 의한 효율적인 영상 부호화 (Karhunen - Loeve Transform -Classified Vector Quantization for Efficient Image Coding)

  • 김태용;최흥문
    • 전자공학회논문지B
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    • 제33B권11호
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    • pp.44-52
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    • 1996
  • This paper proposes a KLT-CVQ scheme using PCNN to improbe the quality of the reconstructed images at a given bit rate. By using the PCNN and classified vector quantization, we exploit the high energy compaction and compelte decorrelation capbilities of the KLT, and the pdf (probability density function) shape and space-filling advantages of the vQ to improve the performance of the proposed hybrid coding technique. In order to preserve the preceptual fetures such as the edge components in the reconstructed images, we classified the input image blocks according to the texture energy measures of the local statistics and vector-coded them adaptively, and thereby reduces the possible edge degradation in the reconstructed images. The results of the computer simulations show that the performance of the proposed KLT-CVQ is higher than that of the KLT-CSQ or the DCT-CVQ in the quality of the reconstructed images at a given bit rate.

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Semiparametric support vector machine for accelerated failure time model

  • Hwang, Chang-Ha;Shim, Joo-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제21권4호
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    • pp.765-775
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    • 2010
  • For the accelerated failure time (AFT) model a lot of effort has been devoted to develop effective estimation methods. AFT model assumes a linear relationship between the logarithm of event time and covariates. In this paper we propose a semiparametric support vector machine to consider situations where the functional form of the effect of one or more covariates is unknown. The proposed estimating equation can be computed by a quadratic programming and a linear equation. We study the effect of several covariates on a censored response variable with an unknown probability distribution. We also provide a generalized approximate cross-validation method for choosing the hyper-parameters which affect the performance of the proposed approach. The proposed method is evaluated through simulations using the artificial example.

Forecasting volatility via conditional autoregressive value at risk model based on support vector quantile regression

  • Shim, Joo-Yong;Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • 제22권3호
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    • pp.589-596
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    • 2011
  • The conditional autoregressive value at risk (CAViaR) model is useful for risk management, which does not require the assumption that the conditional distribution does not vary over time but the volatility does. But it does not provide volatility forecasts, which are needed for several important applications such as option pricing and portfolio management. For a variety of probability distributions, it is known that there is a constant relationship between the standard deviation and the distance between symmetric quantiles in the tails of the distribution. This inspires us to use a support vector quantile regression (SVQR) for volatility forecasts with the distance between CAViaR forecasts of symmetric quantiles. Simulated example and real example are provided to indicate the usefulness of proposed forecasting method for volatility.

Improved Space Vector Modulation Strategy for AC-DC Matrix Converters

  • Liu, Xiao;Zhang, Qingfan;Hou, Dianli;Wang, Siyao
    • Journal of Power Electronics
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    • 제13권4호
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    • pp.647-655
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    • 2013
  • In this paper, an approach to reduce the common-mode voltage and to eliminate narrow pulse for implemented AC-DC matrix converters is presented. An improved space vector modulation (SVM) strategy is developed by replacing the zero space vectors with suitable pairs of active ones. Further, while considering the commutation time, the probability of narrow pulse in the conventional and proposed SVM methods are derived and compared. The advantages of the proposed scheme include: a 50% reduction in the peak value of the common-mode voltage; improved input and output performances; a reduction in the switching loss by a reduced number of switching commutations and a simplified implementation via software. Experimental results are presented to demonstrate the correctness of the theoretical analysis, as well as the feasibility of the proposed strategy.

벡터이득 대자연게임의 해법 (Methods for Solving the Game against Nature with Vector Payoffs)

  • 김여근
    • 한국국방경영분석학회지
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    • 제9권2호
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    • pp.61-68
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    • 1983
  • The traditional theories of games are based on an assumption that the payoffs have a single dimension. In reality, any alternative is likely to imply more than one payoff. This paper deals with the game against nature with vector payoffs. The purpose of this paper is to develop methods for finding the practical optimal strategy in the game against nature with vector payoffs. Under the assumption that a prior probability over the stats of nature is given, this paper shows that a practical optimal strategy in this game can be obtained by applying a entropy method in order to assess the payoff weight and by employing the concept of compromise solutions in order to reduce the non-dominated solutions. When subjective payoff weights are unknown as well as known, these methods can be used. A numerical example is given.

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알고리즘 수정에 의한 홉필드 모델의 성능 개선 (Dummy Stored Memory Algorithm for Hopfield Model)

  • 오상훈;윤태훈;김재창
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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    • pp.41-44
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    • 1987
  • Recently Hopfield proposed a model for content-addressable memory, which has been shown to be capable of storing information in a distributed fashion and determining the nearest-neighbor. Its application is, however, inherently limited to the case that the number of l's in each stored vector is nearly the same as the number of O's in that vector. If not the case, the model has high probability of failure in finding the nearest-neighbor. In this work, a modification of the Hopfield's model, which works well irrespective of the number of l's (or O's) in each stored vector, is suggested.

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다중 거칠기 벡터와 통계적 분류기를 이용한 초음파 간 영상 분류에 관한 연구 (A Study on the Classification of Ultrasonic Liver Images Using Multi Texture Vectors and a Statistical Classifier)

  • 정정원;김동윤
    • 대한의용생체공학회:의공학회지
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    • 제17권4호
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    • pp.433-442
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    • 1996
  • Since one texture property(i.e coarseness, orientation, regularity, granularity) for ultrasound liver ages was not sufficient enough to classify the characteristics of livers, we used multi texture vectors tracted from ultrasound liver images and a statistical classifier. Multi texture vectors are selected among the feature vectors of the normal liver, fat liver and cirrhosis images which have a good separability in those ultrasound liver images. The statistical classifier uses multi texture vectors as input vectors and classifies ultrasound liver images for each multi texture vector by the Bayes decision rule. Then the decision of the liver disease is made by choosing the maximum value from the averages of a posteriori probability for each multi texture vector In our simulation, we obtained higtler correct ratio than that of other methods using single feature vector, for the test set the correct ratio is 94% in the normal liver, 84% in the fat liver and 86% in the cirrhosis liver.

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