• Title/Summary/Keyword: least squares

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EVALUATION OF PARAMETER ESTIMATION METHODS FOR NONLINEAR TIME SERIES REGRESSION MODELS

  • Kim, Tae-Soo;Ahn, Jung-Ho
    • Journal of applied mathematics & informatics
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    • v.27 no.1_2
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    • pp.315-326
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    • 2009
  • The unknown parameters in regression models are usually estimated by using various existing methods. There are several existing methods, such as the least squares method, which is the most common one, the least absolute deviation method, the regression quantile method, and the asymmetric least squares method. For the nonlinear time series regression models, which do not satisfy the general conditions, we will compare them in two ways: 1) a theoretical comparison in the asymptotic sense and 2) an empirical comparison using Monte Carlo simulation for a small sample size.

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HDR image display combines weighted least square filtering with color appearance model

  • Piao, Meixian;Lee, Kyungjun;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.06a
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    • pp.260-263
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    • 2016
  • Recently high dynamic range imaging technique is hot issue in computer graphic area. We present a progressive tone mapping algorithm, which is based on weighted least squares optimization framework. Our approach combines weighted leastsquaresfiltering with iCAM06, for showing more perceptual high dynamic range images in conventional display, while avoiding visual halo artifacts. We decompose high dynamic range image into base layer and detail layer. The base layer has large scale variation, it is obtained by using weighted least squares filtering, and then the base layer incorporates iCAM06 model. Then, adaptive compression on the base layer according to human visual system. Only the base layer reduces contrast, and preserving detail. The resultshows more perceptual color appearance and preserve fine detail, while avoiding common artifacts.

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ROBUST TEST BASED ON NONLINEAR REGRESSION QUANTILE ESTIMATORS

  • CHOI, SEUNG-HOE;KIM, KYUNG-JOONG;LEE, MYUNG-SOOK
    • Communications of the Korean Mathematical Society
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    • v.20 no.1
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    • pp.145-159
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    • 2005
  • In this paper we consider the problem of testing statistical hypotheses for unknown parameters in nonlinear regression models and propose three asymptotically equivalent tests based on regression quantiles estimators, which are Wald test, Lagrange Multiplier test and Likelihood Ratio test. We also derive the asymptotic distributions of the three test statistics both under the null hypotheses and under a sequence of local alternatives and verify that the asymptotic relative efficiency of the proposed test statistics with classical test based on least squares depends on the error distributions of the regression models. We give some examples to illustrate that the test based on the regression quantiles estimators performs better than the test based on the least squares estimators of the least absolute deviation estimators when the disturbance has asymmetric and heavy-tailed distribution.

Study on the Airfoil Shape Design Optimization Using Database based Genetic Algorithms (데이터베이스 기반 유전 알고리즘을 이용한 효율적인 에어포일 형상 최적화에 대한 연구)

  • Kwon, Jang-Hyuk;Kim, Jin;Kim, Su-Whan
    • Journal of Advanced Marine Engineering and Technology
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    • v.31 no.1
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    • pp.58-66
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    • 2007
  • Genetic Algorithms (GA) have some difficulties in practical applications because of too many function evaluations. To overcome these limitations, an approximated modeling method such as Response Surface Modeling(RSM) is coupled to GAs. Original RSM method predicts linear or convex problems well but it is not good for highly nonlinear problems cause of the average effect of the least square method(LSM). So the locally approximated methods. so called as moving least squares method(MLSM) have been used to reduce the error of LSM. In this study, the efficient evolutionary GAs tightly coupled with RSM with MLSM are constructed and then a 2-dimensional inviscid airfoil shape optimization is performed to show its efficiency.

An Efficient Approach to Circular Curve Fitting of Articulated Manipulators Using Least Squares (최소자승법을 이용한 수직다관절 Manipulator의 원호보간에 관한 효과적인 방법)

  • 김대영;최은재;정원지;서영교;홍형표
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.570-575
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    • 2002
  • This paper presents a new circular curve fitting approach of articulated manipulators, based on pseudoinverses. The paper aims at gaining the interpolation of circle from n data points, under the condition that the fitted circle should pass both a start point and an end point. In this paper, two algorithms of circular interpolation are presented. Prior to circular interpolation, are a spherical fitting should be performed, using least squares. In the first algorithm, the relationship between point data and normal vector on the sphere is used. In the second algorithm. the equation of plane which can be obtained from 3 points, i.e., a start point, an end point, and center of a sphere. The proposed algorithms are show to be efficient by using MATLAB-based simulation.

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An Experimental Study on Realtime Estimation of a Nominal Model for a Disturbance Observer: Recursive Least Squares Approach (실시간 공칭 모델 추정 외란관측기에 관한 실험 연구: 재귀최소자승법)

  • Lee, Sang-Deok;Jung, Seul
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.8
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    • pp.650-655
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    • 2016
  • In this paper, a novel RLS-based DOB (Recursive Least Squares Disturbance Observer) scheme is proposed to improve the performance of DOB for nominal model identification. A nominal model can be generally assumed to be a second order system in the form of a proper transfer function of an ARMA (Autoregressive Moving Average) model. The RLS algorithm for the model identification is proposed in association with DOB. Experimental studies of the balancing control of a one-wheel robot are conducted to demonstrate the feasibility of the proposed method. The performances between the conventional DOB scheme and the proposed scheme are compared.

On the Complex-Valued Recursive Least Squares Escalator Algorithm with Reduced Computational Complexity

  • Kim, Nam-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.5C
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    • pp.521-526
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    • 2009
  • In this paper, a complex-valued recursive least squares escalator filter algorithm with reduced computational complexity for complex-valued signal processing applications is presented. The local tap weight of RLS-ESC algorithm is updated by incrementing its old value by an amount equal to the local estimation error times the local gain scalar, and for the gain scalar, the local input autocorrelation is calculated at the previous time. By deriving a new gain scalar that can be calculated by using the current local input autocorrelation, reduced computational complexity is accomplished. Compared with the computational complexity of the complex-valued version of RLS-ESC algorithm, the computational complexity of the proposed method can be reduced by 50% without performance degradation. The reduced computational complexity of the proposed algorithm is even less than that of the LMS-ESC. Simulation results for complex channel equalization in 64QAM modulation schemes demonstrate that the proposed algorithm has superior convergence and constellation performance.

Block Adjustment and Orthorectification for Multi-Orbit Satellite Images

  • Chen, Liang-Chien;Liu, Chien-Liang;Teo, Tee-Ann
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.888-890
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    • 2003
  • The objective of this investigation is to establish a simple yet effective block adjustment procedure for the orthorectification of multi-orbit satellite images. The major works of the proposed scheme are: (1) adjustment of satellite‘s orbit accurately, (2) calculation of the error vectors for each tie point using digital terrain model and ray tracing technique, (3) refining the orbit using the Least Squares Filtering technique and (4) generation of the orthophotos. In the process of least squares filtering, we use the residual vectors on ground control points and tie points to collocate the orbit. In orthorectification, we use the indirect method to generate the orthoimage. Test areas cover northern Taiwan. Test images are from SPOT 5 satellite. Experimental results indicate that proposed method improves the relative accuracy significantly.

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Gene Selection and Classification by Partial Least Squares and Principal component analysis (부분최소자승법과 주성분분석을 이용한 유전자 선택과 분류)

  • Park, Hoseok;Kim, Hey-Jin;Park, Seugj in;Bang, Sung-Yang
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10a
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    • pp.598-600
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    • 2001
  • DNA chip technology enables us to monitor thousands of gene expressions per sample simultaneously. Typically, DNA microarray data has at least several thousands of variables (genes) wish relatively smal1 number of samples. Thus feature (gene) selection by dimensionality reduction is necessary for efficient data analysis. In this paper we employ the partial least squares (PLS) method for gene selection and the principal component analysis (PCA) method for classification. The useful behavior of the PLS is verified by computer simulations.

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Reliability Based Design Optimization using Moving Least Squares (이동최소자승법을 이용한 신뢰성 최적설계)

  • Park, Jang-Won;Lee, Oh-Young;Im, Jong-Bin;Lee, Soo-Yong;Park, Jung-Sun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.36 no.5
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    • pp.438-447
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    • 2008
  • This study is focused on reliability based design optimization (RBDO) using moving least squares. A response surface is used to derive a limit-state equation for reliability based design optimization. Response surface method (RSM) with least square method (LSM) or Kriging will be used as a response surface. RSM is fast to make the response surface. On the other hand, RSM has disadvantage to make the response surface of nonlinear equation. Kriging can make the response surface in nonlinear equation precisely but needs considerable amount of computations. The moving least square method (MLSM) is made of both methods (RSM with LSM+Kriging). Numerical results by MLSM are compared with those by LMS in Rosenbrock function and six-hump carmel back function. The RBDO of engine duct of smart UAV is pursued in this paper. It is proved that RBDO is useful tool for aerospace structural optimal design problems.