• 제목/요약/키워드: Estimator

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수확예측(收穫豫測) Model의 Multicollinearity 문제점(問題點) 해결(解決)을 위(爲)한 Ridge Regression의 이용(利用) (The Use Ridge Regression for Yield Prediction Models with Multicollinearity Problems)

  • 신만용
    • 한국산림과학회지
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    • 제79권3호
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    • pp.260-268
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    • 1990
  • 수확(收穫) 예측(豫測) model이 multicollinearity 문제점(問題點) 가질때 보다 정확한 추정식(推定式)을 얻기 위하여 두 종류의 ridge estimator와 최소(最小) 자승법(自乘法)(OLS)의 추정치를 비교(比較)하였다. 본 연구(硏究)에서 사용(使用)된 ridge estmator는 Mallows's (1973)Cp-like statistic과 Allens's (1974) PRESS-like statistic 이었다. 위의 세가지 estimator 예측(豫測) 능력(能力) 평가(評賣)는 Matney 등(等)(1988)에 의하여 개발(開發)된 수확(收穫) model을 이용(利用)하여 비교(比較)하였다. 사용되어진 자료(資料)는 미국(美國) 남부(南部) 테에다 소나무 시험림(試驗林)의 총(總)522개(個) plot을 이용(利用)하였다. 두 개(個)의 ridge estimator가 최소(最小) 자승법(自乘法)에 의한 추정치 보다 수확(收穫) 예측(豫測) 능력(能力)이 우수(優秀)하였으며, 특히 Mallows's statistic에 의한 ridge estimator가 가장 우수(優秀)하였다. 따라서 ridge estimator는 수확(收穫) 예측(豫測) model의 독립(獨立) 변수(變數) 간(間)에 multicollinearity 문제점(問題點)이 있을 때 최소(最小) 자승법(自乘法)에 의 한 추정치를 대치(代置)할 수 있는 estimator로서 추천(推薦)할 수 있었다.

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Carrier Frequency Offset Estimation Using ESPRIT for the Interleaved OFDMA Uplink Systems

  • Lee, Jung-Hoon;Lee, Sung-Eun;Hong, Dae-Sik
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2005년도 추계종합학술대회
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    • pp.175-178
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    • 2005
  • In this paper, a carrier frequency offset (CFO) estimator is proposed for the interleaved OFDMA uplink systems. It is based on the estimation of signal parameters via rotational invariance technique (ESPRIT). Compared with the Cao's estimator, the proposed estimator has low computational complexity. Simulation results demonstrate that the proposed estimator performs better than Cao's estimator at the relatively low SNR region. Hence, the proposed estimator is more applicable to the practical environments than the Cao’s estimator.

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차량 전복 방지를 위한 강건한 롤 상태 추정기 설계 (Design of a Robust Estimator for Vehicle Roll State for Prevention of Vehicle Rollover)

  • 박지인;이경수
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.1103-1108
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    • 2007
  • This paper describes a robust model-based roll state estimator for application to the detection of impending vehicle rollover. The roll state estimator is based on a 2-D bicycle model and a roll model to estimate the maneuver-induced vehicle roll motion. The measurement signals are lateral acceleration, yaw rate, steering angle, and vehicle speed. Vehicle mass is adapted to obtain robust performance of the estimator. Computer simulation is conducted to evaluate the proposed roll state estimator by using a validated vehicle simulator. It is shown that the roll state estimator shows robust performance without exact vehicle mass information.

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An On-line Rotor Resistance Estimator for Induction Machine Drives

  • Kwon, Chun-Ki
    • Journal of Power Electronics
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    • 제9권3호
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    • pp.354-364
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    • 2009
  • Rotor resistance variation due to changing rotor temperature is a significant issue in the design of induction motor controls. In this work, a new on-line rotor resistance estimator is proposed based on an alternate qd induction machine model which provides better mathematical representation of an induction machine than the classical qd model (which uses constant parameters). This is because the former simultaneously includes leakage saturation, magnetizing path saturation, and distributed circuit effects in the rotor conductors. The comparisons via computer simulation studies show the ability of the proposed estimator to accurately track rotor resistance variation. For the experimental studies, due to the difficulty in measuring the actual rotor resistance, comparison of the controller performance using the proposed estimator, the classical qd model based estimator, and no estimator is made.

A High Breakdown and Efficient GM-Estimator in Linear Models

  • Song, Moon-Sup;Park, Changsoon;Nam, Ho-Soo
    • Journal of the Korean Statistical Society
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    • 제25권4호
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    • pp.471-487
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    • 1996
  • In this paper we propose an efficient scoring type one-step GM-estimator, which has a bounded influence function and a high break-down point. The main point of the estimator is in the weighting scheme of the GM-estimator. The weight function we used depends on both leverage points and residuals So we construct an estimator which does not downweight good leverage points Unider some regularity conditions, we compute the finite-sample breakdown point and prove asymptotic normality Some simulation results are also presented.

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A note on SVM estimators in RKHS for the deconvolution problem

  • Lee, Sungho
    • Communications for Statistical Applications and Methods
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    • 제23권1호
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    • pp.71-83
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    • 2016
  • In this paper we discuss a deconvolution density estimator obtained using the support vector machines (SVM) and Tikhonov's regularization method solving ill-posed problems in reproducing kernel Hilbert space (RKHS). A remarkable property of SVM is that the SVM leads to sparse solutions, but the support vector deconvolution density estimator does not preserve sparsity as well as we expected. Thus, in section 3, we propose another support vector deconvolution estimator (method II) which leads to a very sparse solution. The performance of the deconvolution density estimators based on the support vector method is compared with the classical kernel deconvolution density estimator for important cases of Gaussian and Laplacian measurement error by means of a simulation study. In the case of Gaussian error, the proposed support vector deconvolution estimator shows the same performance as the classical kernel deconvolution density estimator.

A Study on Kernel Type Discontinuity Point Estimations

  • Huh, Jib
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.929-937
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    • 2003
  • Kernel type estimations of discontinuity point at an unknown location in regression function or its derivatives have been developed. It is known that the discontinuity point estimator based on $Gasser-M\ddot{u}ller$ regression estimator with a one-sided kernel function which has a zero value at the point 0 makes a poor asymptotic behavior. Further, the asymptotic variance of $Gasser-M\ddot{u}ller$ regression estimator in the random design case is 1.5 times larger that the one in the corresponding fixed design case, while those two are identical for the local polynomial regression estimator. Although $Gasser-M\ddot{u}ller$ regression estimator with a one-sided kernel function which has a non-zero value at the point 0 for the modification is used, computer simulation show that this phenomenon is also appeared in the discontinuity point estimation.

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시퀀스 추정기를 사용하는 CDMA 파일럿 수신회로 (CDMA Pilot Receiving Circuit Using Sequence Estimator)

  • 이성민
    • 한국군사과학기술학회지
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    • 제9권4호
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    • pp.32-38
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    • 2006
  • In this paper a sequence estimator of CDMA communication system is suggested. A sequence estimator uses Galois Field operation. A sequence estimator can provide another CDMA pilot signal which is un-modulated spreaded signal. A estimated sequence signal and received signal have no correlation. Tow signals can be summed using MRC(maximal ratio combine) method. The stronger signal can be added as a larger ratio, but the weaker signal can be added as a smaller ratio. We can distinguish strong signal using SNR estimator. Therefore it is possible to receive an additional pilot signal, and to support more reliable communications by using sequence estimator.

유도전동기의 속도 센서리스 제어를 위한 지능형 속도 추정기의 설계 (Design of Intelligent Speed Estimator for Speed Sensorless Control of Induction Motor)

  • 박진수;최성대;김상훈;고봉운;남문현;김낙교
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 하계학술대회 논문집 D
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    • pp.2304-2306
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    • 2004
  • This paper proposes an Intelligent Speed Estimator in order to realize the speed-sensorless vector control of an induction motor. Intelligent Speed Estimator used Model Reference Adaptive System which has Fuzzy-Neural adaptive mechanism as Speed Estimation method. The Intelligent Speed Estimator estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. The Intelligent Speed Estimator reduces the error of the rotor flux between the voltage flux model and the current flux model using the error and the change of error as input of the Estimator. The computer simulation is executed to verify the propriety and the effectiveness of the proposed speed estimator.

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An Efficient Mallows-Type One-Step GM-Estimator in linear Models

  • Song, Moon-Sup;Park, Changsoon;Nam, Ho-Soo
    • Journal of the Korean Statistical Society
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    • 제27권3호
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    • pp.369-383
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    • 1998
  • This paper deals with a robust regression estimator. We propose an efficient one-step GM-estimator, which has a bounded influence function and a high breakdown point. The main idea of this paper is to use the Mallows-type weights which depend on both the predictor variables and the residuals from a high breakdown initial estimator. The proposed weighting scheme severely downweights the bad leverage points and slightly downweights the good leverage points. Under some regularity conditions, we compute the finite-sample breakdown point and prove the asymptotic normality. Some simulation results and a numerical example are also presented.

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