• Title/Summary/Keyword: Multi-estimator

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바이어스추정을 기반으로 한 위치추정의 오차회복 (Localization Error Recovery Based on Bias Estimation)

  • 김용식;이재훈;김봉근;오바 코타로;오야 아키히사
    • 로봇학회논문지
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    • 제4권2호
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    • pp.112-120
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    • 2009
  • In this paper, a localization error recoverymethod based on bias estimation is provided for outdoor localization of mobile robot using different-type sensors. In the previous data integration method with DGPS, it is difficult to localize mobile robot due to multi-path phenomena of DGPS. In this paper, fault data due to multi-path phenomena can be recovered by bias estimation. The proposed data integration method uses a Kalman filter based estimator taking into account a bias estimator and a free-bias estimator. A performance evaluation is shown through an outdoor experiment using mobile robot.

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Asymptotic Theory for Multi-Dimensional Mode Estimator

  • Kim, Jean-Kyung
    • Journal of the Korean Statistical Society
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    • 제23권2호
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    • pp.251-269
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    • 1994
  • In this paper we extend Kim and Pollard's cube root asymptotics to other rates of convergence, to establish an asymptotic theory for a multidimensional mode estimator based on uniform kernel with shrinking bandwidths. We obtain rates of convergence depending on shrinking rates of bandwidth and non-normal limit distributions. Optimal decreasing rates of bandwidth are discussed.

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선형 스위칭 시스템의 관측기 기반 제어 (Observer-based Control for Switched Linear Systems)

  • 염동회;임기홍;최진영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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    • pp.92-94
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    • 2004
  • In the previous work, we proposed a new stability criterion for the stability of switched linear systems. By the proposed criterion, we could simply check the stability of switched linear systems because the criterion is applicable to each individual subsystem without need to consider the overall system. Using this criterion, we provided the methods that design a state feedback control when full states are available. In this paper, we apply the same criterion to the case when full states are not available. Unlike existing method such as dwelling time analysis, the proposed method is suitable to a fast switching process because there is no need to consider dwelling time. And we can easily achieve designing multi-controller, multi-estimator, and the supervisor by means of the proposed method.

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디지털 비디오 방송 시스템에서의 파일럿을 이용한 반복적 주파수 옵셋 추정방법 (Pilot-Aided Iterative Frequency Offset Estimation for Digital Video Broadcasting Systems)

  • 이경택;서종수
    • 한국통신학회논문지
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    • 제32권5A호
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    • pp.484-489
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    • 2007
  • OFDM(orthogonal frequency division multiplexing) 시스템은 시간 동기 및 주파수 옵셋 추정 오차에 따라 시스템 성능이 좌우된다. 본 논문에서는, OFDM을 기반으로 한 디지털 비디오 방송(digital video broadcasting) 시스템을 위한 향상된 정수배 주파수 옵셋 추정 방법을 제안한다. 제안된 정수배 주파수 옵셋 추정기는 기존의 ML 추정기에 다단계 추정 방법을 적용하여 개선한 방법이다. 실험 결과를 통해, 제안된 주파수 옵셋 추정 방법이 기존의 ML 추정기에 비해 적은 연산량으로 향상된 주파수 옵셋 추정 성능을 가진다.

An improvement of estimators for the multinormal mean vector with the known norm

  • Kim, Jaehyun;Baek, Hoh Yoo
    • Journal of the Korean Data and Information Science Society
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    • 제28권2호
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    • pp.435-442
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    • 2017
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}$ (p ${\geq}$ 3) under the quadratic loss from multi-variate normal population. We find a James-Stein type estimator which shrinks towards the projection vectors when the underlying distribution is that of a variance mixture of normals. In this case, the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is known where K is a projection vector with rank(K) = q. The class of this type estimator is quite general to include the class of the estimators proposed by Merchand and Giri (1993). We can derive the class and obtain the optimal type estimator. Also, this research can be applied to the simple and multiple regression model in the case of rank(K) ${\geq}2$.

Multi-Level Rotation Sampling Designs and the Variances of Extended Generalized Composite Estimators

  • Park, You-Sung;Park, Jai-Won;Kim, Kee-Whan
    • 한국조사연구학회:학술대회논문집
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    • 한국조사연구학회 2002년도 추계학술대회 발표논문집
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    • pp.255-274
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    • 2002
  • We classify rotation sampling designs into two classes. The first class replaces sample units within the same rotation group while the second class replaces sample units between different rotation groups. The first class is specified by the three-way balanced design which is a multi-level version of previous balanced designs. We introduce an extended generalized composite estimator (EGCE) and derive its variance and mean squared error for each of the two classes of design, cooperating two types of correlations and three types of biases. Unbiased estimators are derived for difference between interview time biases, between recall time biases, and between rotation group biases. Using the variance and mean squared error, since any rotation design belongs to one of the two classes and the EGCE is a most general estimator for rotation design, we evaluate the efficiency of EGCE to simple weighted estimator and the effects of levels, design gaps, and rotation patterns on variance and mean squared error.

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층화 다단계 샘플링에서 설계 기반 분산추정 (Design-based Variance Estimation under stratified Multi-stage Sampling)

  • 김규성
    • 한국조사연구학회:학술대회논문집
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    • 한국조사연구학회 2001년도 춘계학술대회
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    • pp.59-71
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    • 2001
  • 층화 다단계 샘플링에서 모총계 추정을 위하여 동질선형추정량을 고려하고, 이 추정량의 설계기반분산추정법을 고찰하였다. 한 방법은 분산을 일단계 분산과 이단계 분산으로 구분하여 각 층에서 각각을 비편향 추정하는 방법이고, 또 다른 방법은 이단계 표본에서 선정한 부차표본을 이용하여 일단계 분산만을 추정하여 전체분산을 비편향 추정하는 방법이다. 전자는 이단계 분산이 추정 가능할 때 이용하기 좋으며 후자는 이단계 분산을 추정할 수 없을 때 용이하게 쓸 수 있다. 각각의 추정법에 대하여 동질선형추정량에 대한 비음 비편향 분산 추정량의 형태를 제안하였다. 향후 실제 조사에서 본 논문에서 제안한 분산추정법이 효과적으로 사용될 수 있기를 기대한다.

신경망 기법을 이용한 스튜어트 플랫폼의 순기구학 추정 (The Estimation for the Forward Kinematic Solution of Stewart Platform Using the Neural Network)

  • 이형상;한명철;이민철
    • 한국정밀공학회지
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    • 제16권8호
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    • pp.186-192
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    • 1999
  • This paper introduces a study of a method for the forward kinematic analysis, which finds the 6 DOF motions and velocities from the given six cylinder lengths in the Stewart platform. From the viewpoints of kinematics, the solution for the inverse kinematic is easily found by using the vectors of the links which are composed of the joint coordinates in base and plate frames, to act contrary to the serial manipulator, but forward kinematic is difficult because of the nonlinearity and complexity of the Stewart platform dynamic equation with the multi-solutions. Hence we, first in this study, introduce the linear estimator using the Luenberger's observer, and the estimator using the nonlinear measured model for the forward kinematic solutions. But it is difficult to find the parameter of the design for the estimation gain or to select the estimation gain and the constant steady state error exists. So this study suggests the estimator with the estimation gain to be learned by the neural network with the structure of multi-perceptron and the learning method using back propagation and shows the estimation performance using the simulation.

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층화 다단계 샘플링에서 설계 기반 분산추정 (Design-based Variance Estimation under Stratified Multi-stage Sampling)

  • 김규성
    • 한국조사연구학회지:조사연구
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    • 제2권1호
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    • pp.59-71
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    • 2001
  • 층화 다단계 샘플링에서 모총계 추정을 위하여 동질선형추정량을 고려하고. 이 추정량의 설계기반 분산추정법을 고찰하였다. 한 방법은 분산을 일단계 분산과 이단계 분산으로 구분하여 각 층에서 각각을 비편향 추정하는 방법이고, 또 다른 방법은 이단계 표본에서 선정한 부하표본을 이용하여 일단계 분산만을 추정하여 전체분산을 비편향 추정하는 방법이다. 전자는 이단계 분산이 추정 가능할 때 이용하기 좋으며 후자는 이단계 분산을 추정할 수 없을 때 용이하게 쓸 수 있다. 각각의 추정법에 대하여 동질선형추정량에 대한 비음 비편향 분산 추정량의 형태를 제안하였다. 향 후 실제 조사에서 본 논문에서 제안한 분산추정법이 효과적으로 사용될 수 있기를 기대한다.

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Multi-Level Rotation Designs for Unbiased Generalized Composite Estimator

  • Park, You-Sung;Choi, Jai-Won;Kim, Kee-Whan
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2003년도 추계 학술발표회 논문집
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    • pp.123-130
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    • 2003
  • We define a broad class of rotation designs whose monthly sample is balanced in interview time, level of recall, and rotation group, and whose rotation scheme is time-invariant. The necessary and sufficient conditions are obtained for such designs. Using these conditions, we derive a minimum variance unbiased generalized composite estimator (MVUGCE). To examine the existence of time-in-sample bias and recall bias, we also propose unbiased estimators and their variances. Numerical examples investigate the impacts of design gap, non-sampling error sources, and two types of correlations on the variance of MVUGCE.

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