• 제목/요약/키워드: least-squares estimation

검색결과 571건 처리시간 0.162초

극성 판별이 가능한 최소 제곱법 기반의 IPMSM 회전자 초기 위치 추정 (Initial Rotor Position Estimation of an IPMSM Based on Least Squares Approximation with a Polarity Identification)

  • 김건영;박영수;이교범
    • 전력전자학회논문지
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    • 제23권1호
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    • pp.72-75
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    • 2018
  • An initial rotor position estimation method is proposed in this study for an interior permanent-magnet synchronous motor without a resolver or an absolute encoder. This method uses least squares approximation to estimate the initial rotor position. The magnetic polarity is identified by injection of short pulses. The proposed estimation process is robust because it does not require complex signal processing that depends on the performance of a digital filter. In addition, it can be applied to various servo systems because it does not require additional hardware. Experimental results validate the effectiveness of the proposed method using a standard industrial servomotor with interior-permanent magnets.

정다각형 배열 광마우스를 이용한 최소 자승 속도 추정법에 대한 민감도 분석 (Sensitivity Analysis of Least Squares Velocity Estimation Using a Regular Polygonal Array of Optical Mice)

  • 김성복;정일화;이상협
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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    • pp.145-146
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    • 2007
  • This paper presents the sensitivity analysis of the leasst qsuares velocity estimation of an omnidirectional mobile robot using a regular polygonal array of optical mice. First, the velocity kinematics from a mobile robot to an array of optical mice is derived as an overdetermined linear system. Then, for a given set of optical mouse readings, the least squares velocity estimation of a mobile robot is obtained as the simple average. Finally, the sensitivity analysis of the proposed least squares velocity estimation to imprecise installation is made.

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A Generalized Partly-Parametric Additive Risk Model

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제17권2호
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    • pp.401-409
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    • 2006
  • We consider a generalized partly-parametric additive risk model which generalizes the partly parametric additive risk model suggested by McKeague and Sasieni (1994). As an estimation method of this model, we propose to use the weighted least square estimation, suggested by Huffer and McKeague (1991), for Aalen's additive risk model by a piecewise constant risk. We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least squares method.

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비대칭 오차모형하에서의 회귀기울기에 대한 적합된 L-추정법 (Adaptive L-estimation for regression slope under asymmetric error distributions)

  • 한상문
    • 응용통계연구
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    • 제6권1호
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    • pp.79-93
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    • 1993
  • 회귀모형에 있어서의 Ruppert와 Carroll의 절사 회귀 추정법을 확장하여 회귀 분위수에 의 한 두 개의 두분으로 관측치를 분할하여 각 부분마다 가중치를 달리 부여하는 방법으로 적 합된 L-추정법을 제안하였다. 이 제안된 L-추정법은 특히 비대칭인 오차분포하에서 좋은 효율을 가지고 있었다.

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PLS를 활용한 고차요인구조 추정방법의 비교 (A Comparison of Estimation Approaches of Structural Equation Model with Higher-Order Factors Using Partial Least Squares)

  • 손기혁;전영호;옥창수
    • 산업경영시스템학회지
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    • 제36권4호
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    • pp.64-70
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    • 2013
  • Estimation approaches for casual relation model with high-order factors have strict restrictions or limits. In the case of ML (Maximum Likelihood), a strong assumption which data must show a normal distribution is required and factors of exponentiation is impossible due to the uncertainty of factors. To overcome this limitation many PLS (Partial Least Squares) approaches are introduced to estimate the structural equation model including high-order factors. However, it is possible to yield biased estimates if there are some differences in the number of measurement variables connected to each latent variable. In addition, any approach does not exist to deal with general cases not having any measurement variable of high-order factors. This study compare several approaches including the repeated measures approach which are used to estimate the casual relation model including high-order factors by using PLS (Partial Least Squares), and suggest the best estimation approach. In other words, the study proposes the best approach through the research on the existing studies related to the casual relation model including high-order factors by using PLS and approach comparison using a virtual model.

Motion analysis within non-rigid body objects in satellite images using least squares matching

  • Hasanlou M.;Saradjian M.R.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.47-51
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    • 2005
  • Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

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기울기 평균 벡터를 사용한 가변 스텝 최소 자승 알고리즘과 시변 망각 인자를 사용한 시변 음향 채널 추정 (An time-varying acoustic channel estimation using least squares algorithm with an average gradient vector based a self-adjusted step size and variable forgetting factor)

  • 임준석
    • 한국음향학회지
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    • 제38권3호
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    • pp.283-289
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    • 2019
  • RLS(Recursive-least-squares) 알고리즘은 수렴성이 좋고, 수렴 후 오차 수준도 우수한 것으로 알려져 있다. 그러나 알고리즘 내에 역행렬 계산이 포함되어 수치적 불안정성을 나타내는 단점도 있다. 본 논문에서는 언급한 불안정성을 회피하기 위해서 역행렬이 없지만 수렴성이 유사한 알고리즘을 제안한다. 이를 위해서 기울기 평균 벡터를 사용한 가변 스텝 최소 자승 알고리즘을 사용한다. 또 시변 채널 추정에 우수한 성능을 내기 위해서 계산량이 적은 가변 망각인자를 도입한다. 시뮬레이션을 통해서 기존 RLS와의 성능을 비교하고 그 유사성을 보인다. 또 시변 채널에서 가변 망각인자의 우수성도 보인다.

A New Recursive Least-Squares Algorithm based on Matrix Pseudo Inverses (ICCAS 2003)

  • Quan, Zhonghua;Han, Soo-Hee;Kwon, Wook-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.927-931
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    • 2003
  • In this paper, a new Recursive Least-Squares(RLS) algorithm based on matrix pseudo-inverses is presented. The aim is to use the proposed new RLS algorithm for not only the over-determined but also the under-determined estimation problem. Compared with previous results, e.g., Jie Zhou et al., the derivation of the proposed recursive form is much easier, and the recursion form is also much simpler. Furthermore, it is shown by simulations that the proposed RLS algorithm is more efficient and numerically stable than the existing algorithms.

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Estimation of viscous and Coulomb damping from free-vibration data by a least-squares curve-fitting analysis

  • Slemp, Wesley C.H.;Hallauer, William L. Jr.;Kapania, Rakesh K.
    • Smart Structures and Systems
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    • 제4권3호
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    • pp.279-290
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    • 2008
  • The modeling and parameter estimation of a damped one-degree-of-freedom mass-spring system is examined. This paper presents a method for estimating the system parameters (damping coefficients and natural frequency) from measured free-vibration motion of a system that is modeled to include both subcritical viscous damping and kinetic Coulomb friction. The method applies a commercially available least-squares curve-fitting software function to fit the known solution of the equations of motion to the measured response. The method was tested through numerical simulation, and it was applied to experimental data collected from a laboratory mass-spring apparatus. The mass of this apparatus translates on linear bearings, which are the primary source of light inherent damping. Results indicate that the curve-fitting method is effective and accurate for both perfect and noisy measurements from a lightly damped mass-spring system.

Multiple Structural Change-Point Estimation in Linear Regression Models

  • Kim, Jae-Hee
    • Communications for Statistical Applications and Methods
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    • 제19권3호
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    • pp.423-432
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    • 2012
  • This paper is concerned with the detection of multiple change-points in linear regression models. The proposed procedure relies on the local estimation for global change-point estimation. We propose a multiple change-point estimator based on the local least squares estimators for the regression coefficients and the split measure when the number of change-points is unknown. Its statistical properties are shown and its performance is assessed by simulations and real data applications.