• 제목/요약/키워드: Least square criterion

검색결과 50건 처리시간 0.027초

LEAST-SQUARE SWITCHING PROCESS FOR ACCURATE AND EFFICIENT GRADIENT ESTIMATION ON UNSTRUCTURED GRID

  • SEO, SEUNGPYO;LEE, CHANGSOO;KIM, EUNSA;YUNE, KYEOL;KIM, CHONGAM
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제24권1호
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    • pp.1-22
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    • 2020
  • An accurate and efficient gradient estimation method on unstructured grid is presented by proposing a switching process between two Least-Square methods. Diverse test cases show that the gradient estimation by Least-Square methods exhibit better characteristics compared to Green-Gauss approach. Based on the investigation, switching between the two Least-Square methods, whose merit complements each other, is pursued. The condition number of the Least-Square matrix is adopted as the switching criterion, because it shows clear correlation with the gradient error, and it can be easily calculated from the geometric information of the grid. To illustrate switching process on general grid, condition number is analyzed using stencil vectors and trigonometric relations. Then, the threshold of switching criterion is established. Finally, the capability of Switching Weighted Least-Square method is demonstrated through various two- and three-dimensional applications.

Estimation of Ridge Regression Under the Integrate Mean Square Error Cirterion

  • Yong B. Lim;Park, Chi H.;Park, Sung H.
    • Journal of the Korean Statistical Society
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    • 제9권1호
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    • pp.61-77
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    • 1980
  • In response surface experiments, a polynomial model is often used to fit the response surface by the method of least squares. However, if the vectors of predictor variables are multicollinear, least squares estimates of the regression parameters have a high probability of being unsatisfactory. Hoerland Kennard have demonstrated that these undesirable effects of multicollinearity can be reduced by using "ridge" estimates in place of the least squares estimates. Ridge regrssion theory in literature has been mainly concerned with selection of k for the first order polynomial regression model and the precision of $\hat{\beta}(k)$, the ridge estimator of regression parameters. The problem considered in this paper is that of selecting k of ridge regression for a given polynomial regression model with an arbitrary order. A criterion is proposed for selection of k in the context of integrated mean square error of fitted responses, and illustrated with an example. Also, a type of admissibility condition is established and proved for the propose criterion.criterion.

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전기 임피던스 단층촬영을 위한 지수적으로 가중된 최소자승법을 이용한 수정된 조정 Newton-Raphson 알고리즘 (Regularized Modified Newton-Raphson Algorithm for Electrical Impedance Tomography Based on the Exponentially Weighted Least Square Criterion)

  • 김경연;김봉석
    • 전기전자학회논문지
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    • 제4권2호
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    • pp.249-256
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    • 2000
  • 전기 임피던스 단층촬영에서는, 각기 다른 주입 전류패턴에 의해 유기된 경계면의 전압 값을 이용하여 다양한 복원 알고리즘에 의해 물체의 내부 저항률(전도율) 분포를 추정한다. 본 논문에서는, 부가적인 사전 정보를 soft 제약조건으로 비용함수에 추가하고, 비용함수의 가중행렬을 지수적으로 가중된 최소자승법에 근거하여 선택하는 수정된 조정 Newton-Raphson(mNR) 법을 제안한다. 32채널에 대한 컴퓨터 시뮬레이션 결과, 제안된 방법은 기존의 조정 mNR 법에 비해 계산부담은 약간 증가하지만 복원성능이 개선됨을 보인다.

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역문제에 의한 구조물의 실동하중 해석 (Analysis of Practical Dynamic Force of Structure with Inverse Problem)

  • 송준혁;노홍길;김홍건;유효선;강희용;양성모
    • 한국공작기계학회논문집
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    • 제13권2호
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    • pp.75-80
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    • 2004
  • Vehicle structures are composed of many substructure connected to one another by various types of mechanical joints. In vehicle engineering it is important to study these connected structures under various dynamic forces for the evaluations of fatigue life and stress concentration exactly. It is difficult to obtain the accurate load history of specified positions because of the errors such as modeling, measurement and etc. In the beginning of design exact load data are actually necessary for the fatigue strength and life analysis to minimize the cost and time of designing. In this paper, the procedure of practical dynamic force determination is developed by the combination of the principal stresses of F. E. Analysis and experiment. Least square pseudo inverse matrix is adopted to obtain in inverse matrix of analyzed stresses matrix. The error minimization method utilizes the inaccurate measured error and the shifting error that the whole data is stiffed over real data. The least square criterion is adopted to avoid these non. Finally, to verify the proposed procedure, a bus is analyzed. This measurement and prediction technology can be extended to the structural modification of any geometric shape in complex structure.

제한된 최소 자승 오차 기준에 의한 다양한 FIR 필터 구현 (Implementation of Various FIR Filters using Constrained Least Square Criterion)

  • 홍승억;김중규
    • 전자공학회논문지S
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    • 제35S권10호
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    • pp.175-185
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    • 1998
  • 본 논문에서는 Adams에 의해 제안된 제한된 최소 자승 오차 기준에 의한 FIR 필터 설계 방법을 기초로 하여 저역 통과 필터 외의 다른 여러 가지 필터를 설계할 수 있는 방법론을 제시하였다. 이 방법에 의한 설계는 기존의 자승 오차 최소화 방법과 최대 오차 최소화 방법의 혼합된 형태로써 오차 기준으로 자승 오차와 최대 오차 두 가지를 동시에 고려하게 되며, 최고 이득, 전이 대역폭, 자승 오차 세가지가 모두 만족될 때만 그 해 즉, 임펄스 응답을 찾을 수 있게 된다. 이때 최적화 과정에서는 다중 교환 알고리즘을 이용하였다. 본 논문은 위의 두 중요 오차 기준의 상호 보완을 통하여 다중 대역 통과 필터, 미분기 및 Hilbert 변환기등의 최적 설계에 적용할 수 있는 방법에 대해 고찰하였으며, 그 결과 제한된 최소 자승 오차 기준에 의한 설계 방법이 단순한 저역 통과 필터 뿐만이 아니라 여러 가지 다양한 FIR 필터 설계에 있어서도 그 우수함을 증명할 수 있었다.

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A modified partial least squares regression for the analysis of gene expression data with survival information

  • Lee, So-Yoon;Huh, Myung-Hoe;Park, Mira
    • Journal of the Korean Data and Information Science Society
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    • 제25권5호
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    • pp.1151-1160
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    • 2014
  • In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

KLT를 이용한 AR 스펙트럼 추정기법에 관한 연구 (A new AR power spectral estimation technique using the Karhunen-Loeve Transform)

  • 공성곤;양흥석
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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    • pp.134-136
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    • 1986
  • In this paper, a new power spectral estimation technique is presented. At first, by transforming the original data with the Karhunen-Loeve Transform(KLT), we can reduce the amount of the redundant information. Next, by modeling the transformed data by means of the autoregressive(AR) model and then applying the least-squares parameter estimation algorithm to this model, even more accurate spectrum estimates can be obtained. The KLT is the optimum transform for signal representation with respect to the mean-square error criterion. And the least-squares method is used to overcome the inherent shortcomings of popular burg algorithm.

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Performance of the adaptive LMAT algorithm for various noise densities in a system identification mode

  • 이영환;김상덕;조성호
    • 한국통신학회논문지
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    • 제23권8호
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    • pp.1984-1989
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    • 1998
  • Convergence properties of the stochastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criterion is presented.In particular, the performnce of the algorithmis examined and compared with least mena square (LMS) algorithm for several different probability densities of the measurement noisein a system identification mode. It is observedthat the LMAT algorithm outperforms the LMS algorithm for most of the noise probability densities, except for the case of the exponentially distributed noise.

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Multi-Criteria decision making based on fuzzy measure

  • Sun, Yan;Feng, Di
    • 중소기업융합학회논문지
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    • 제3권2호
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    • pp.19-25
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    • 2013
  • 치명적인 사고를 막기 위해 드라이버 졸음 (DD)를 검출하는 다양한 최근 방법이 제안되고있다. 본 논문은 운전자의 눈에 폐쇄 속도를 모니터링 할 수 있는 기능을 AdaBoost 기반 물체 검출 알고리즘에 적용한 DD 탐지 시스템 구현에서 하드웨어/소프트웨어 공동 설계 방법을 제안한다. 소프트웨어 구성 요소는 DD 검출 알고리즘 중에서 필요한 기능성을 완전하게 달성하기 위해 전체적인 제어 및 논리 연산을 구현한다. 반면, 본 연구에서는 DD 검출 알고리즘의 중요한 기능은 처리를 가속화하기 위해 맞춤형 하드웨어 구성 요소를 통해 가속된다. 하드웨어/소프트웨어 아키텍처는 비디오 도터 보드와 알테라 DE2 보드에 구현되었습니다. 제안 된 구현의 성능을 평가하고 몇 가지 최근의 작품을 벤치마킹했다.

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Classical and Bayesian methods of estimation for power Lindley distribution with application to waiting time data

  • Sharma, Vikas Kumar;Singh, Sanjay Kumar;Singh, Umesh
    • Communications for Statistical Applications and Methods
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    • 제24권3호
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    • pp.193-209
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    • 2017
  • The power Lindley distribution with some of its properties is considered in this article. Maximum likelihood, least squares, maximum product spacings, and Bayes estimators are proposed to estimate all the unknown parameters of the power Lindley distribution. Lindley's approximation and Markov chain Monte Carlo techniques are utilized for Bayesian calculations since posterior distribution cannot be reduced to standard distribution. The performances of the proposed estimators are compared based on simulated samples. The waiting times of research articles to be accepted in statistical journals are fitted to the power Lindley distribution with other competing distributions. Chi-square statistic, Kolmogorov-Smirnov statistic, Akaike information criterion and Bayesian information criterion are used to access goodness-of-fit. It was found that the power Lindley distribution gives a better fit for the data than other distributions.