• 제목/요약/키워드: least-squares problems

검색결과 185건 처리시간 0.026초

통계적 오차보상 기법을 이용한 센서 네트워크에서의 RDOA 측정치 기반의 표적측위 (Stochastic Error Compensation Method for RDOA Based Target Localization in Sensor Network)

  • 최가형;나원상;박진배;윤태성
    • 전기학회논문지
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    • 제59권10호
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    • pp.1874-1881
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    • 2010
  • A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

Modeling mechanical strength of self-compacting mortar containing nanoparticles using wavelet-based support vector machine

  • Khatibinia, Mohsen;Feizbakhsh, Abdosattar;Mohseni, Ehsan;Ranjbar, Malek Mohammad
    • Computers and Concrete
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    • 제18권6호
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    • pp.1065-1082
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    • 2016
  • The main aim of this study is to predict the compressive and flexural strengths of self-compacting mortar (SCM) containing $nano-SiO_2$, $nano-Fe_2O_3$ and nano-CuO using wavelet-based weighted least squares-support vector machines (WLS-SVM) approach which is called WWLS-SVM. The WWLS-SVM regression model is a relatively new metamodel has been successfully introduced as an excellent machine learning algorithm to engineering problems and has yielded encouraging results. In order to achieve the aim of this study, first, the WLS-SVM and WWLS-SVM models are developed based on a database. In the database, nine variables which consist of cement, sand, NS, NF, NC, superplasticizer dosage, slump flow diameter and V-funnel flow time are considered as the input parameters of the models. The compressive and flexural strengths of SCM are also chosen as the output parameters of the models. Finally, a statistical analysis is performed to demonstrate the generality performance of the models for predicting the compressive and flexural strengths. The numerical results show that both of these metamodels have good performance in the desirable accuracy and applicability. Furthermore, by adopting these predicting metamodels, the considerable cost and time-consuming laboratory tests can be eliminated.

비선형계획법을 이용한 대규모 선형계획해법의 개발 (Development of Nonlinear Programming Approaches to Large Scale Linear Programming Problems)

  • 장수영
    • 대한산업공학회지
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    • 제17권2호
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    • pp.131-142
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    • 1991
  • The concept of criterion function is proposed as a framework for comparing the geometric and computational characteristics of various nonlinear programming approaches to linear programming such as the method of centers, Karmakar's algorithm and the gravitational method. Also, we discuss various computational issues involved in obtaining an efficient parallel implementation of these methods. Clearly, the most time consuming part in solving a linear programming problem is the direction finding procedure, where we obtain an improving direction. In most cases, finding an improving direction is equivalent to solving a simple optimization problem defined at the current feasible solution. Again, this simple optimization problem can be seen as a least squares problem, and the computational effort in solving the least squares problem is, in fact, same as the effort as in solving a system of linear equations. Hence, getting a solution to a system of linear equations fast is very important in solving a linear programming problem efficiently. For solving system of linear equations on parallel computing machines, an iterative method seems more adequate than direct methods. Therefore, we propose one possible strategy for getting an efficient parallel implementation of an iterative method for solving a system of equations and present the summary of computational experiment performed on transputer based parallel computing board installed on IBM PC.

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대학수학 경사하강법(gradient descent method) 교수·학습자료 개발 (A Study on the Development of Teaching-Learning Materials for Gradient Descent Method in College AI Mathematics Classes)

  • 이상구;남윤;이재화
    • 한국수학교육학회지시리즈E:수학교육논문집
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    • 제37권3호
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    • pp.467-482
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    • 2023
  • 본 논문에서는 인공지능 알고리즘에서 많이 사용되는 경사하강법(gradient descent method)을 대학수학 강좌에서 인공지능 활용사례로 사용할 수 있도록 연구한 교수·학습 기초자료를 소개한다. 특히 대학 미적분학 수준에서도 가르칠 수 있도록 자세한 개념 설명과 함께 복잡한 함수에 관해서도 쉽게 계산할 수 있도록 파이썬(Python) 기반의 SageMath 코드를 제공한다. 그리고 실제 인공지능 응용과 연계하여 선형회귀에서 발생하는 최소제곱문제를 경사하강법을 활용하여 풀이한 예시도 함께 소개한다. 본 연구는 대학 미적분학 뿐만 아니라 공학수학, 수치해석, 응용수학 등과 같은 고급 수학 과목을 지도하는 다양한 교수자들에게 도움이 될 수 있다.

A surface extension method using several functions

  • 김회섭
    • 한국전산응용수학회:학술대회논문집
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    • 한국전산응용수학회 2003년도 KSCAM 학술발표회 프로그램 및 초록집
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    • pp.3.2-3
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    • 2003
  • We propose a method of surface extension method using several functions. Interpolation theory is well developed in curve and surface. But extrapolation theory is not well developed because it is not unique outside the useful domain. It requires continuous, first derivative, second derivative continuous extension for matching in NC(Numerical Control) machine. In the past, we generate data outside the useful area and refit those data using least squares method. this has some problems which have some errors within the useful area. We keep the useful area and extend the unuseful area by a function

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Design of reduced-order controllers in two-degree-of-freedom control systems

  • Nakamura, T.;Obinata, G.;Inooka, H.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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    • pp.753-758
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    • 1988
  • In this paper, we propose a new method of designing a reduced-order controller for a linear discrete-time system. Firstly, we study a design problem for a two-degree-of-freedom control system with a feedforward controller. Secondly, in order to obtain a reduced-order controller, frequency-weighted least squares approximation problems are considered. Thirdly, we propose a synthesis procedure of a reduced-order controller. Finally, an example is given to illustrate the effectiveness of this proposed method.

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블록기반의 윤곽선 분류를 이용한 윤곽선 보존 영상복원 기법 (Edge-Preserving Image Restoration Using Block-Based Edge Classification)

  • 이상광;호요성
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1998년도 학술대회
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    • pp.33-36
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    • 1998
  • Most image restoration problems are ill-posed and need to e regularized. A difficult task in image regularization is to avoid smoothing of image edges. In this paper, were proposed an edge-preserving image restoration algorithm using block-based edge classification. In order to exploit the local image characteristics, we classify image blocks into edge and no-edge blocks. We then apply an adaptive constrained least squares (CLS) algorithm to eliminate noise around the edges. Experimental results demonstrate that the proposed algorithm can preserve image edges during the regularization process.

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최소자승법을 이용한 Constrained Multichannel FIR 적응 빔 형성 알고리즘 (Constrained Multichannel Adaptive FIR Beamforming Algorithm Based upon Least Squares Method)

  • 김달수;신윤기;박의열
    • 전자공학회논문지A
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    • 제28A권9호
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    • pp.671-679
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    • 1991
  • In adaptive antenna, several models are known according to a prior knowledge about jammer signal. Among those, Frost model with contraint is generally used however it has the problem that convergence speed is slow and that stability is not good. To improve such problems, this paper proposes constrained NLMS algorithm using LS method. In addition, the result obtained by applying this algorithm to Duvall antenna model is compared with that of Frost model.

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TWO DIMENSIONAL VERSION OF LEAST SQUARES METHOD FOR DEBLURRING PROBLEMS

  • Kwon, SunJoo;Oh, SeYoung
    • 충청수학회지
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    • 제24권4호
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    • pp.895-903
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    • 2011
  • A two dimensional version of LSQR iterative algorithm which takes advantages of working solely with the 2-dimensional arrays is developed and applied to the image deblurring problem. The efficiency of the method comparing to the Fourier-based LSQR method and the 2-D version CGLS algorithm methods proposed by Hanson ([4]) is analyzed.

2차원 비압축성 점성유동에 관한 무격자법 기반의 수치해석 (NUMERICAL STUDY ON TWO-DIMENSIONAL INCOMPRESSIBLE VISCOUS FLOW BASED ON GRIDLESS METHOD)

  • 정세민;박종천;허재경
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2009년 춘계학술대회논문집
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    • pp.239-244
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    • 2009
  • The gridless (or meshfree) methods, such as MPS, SPH, FPM an so forth, are feasible and robust for the problems with moving boundary and/or complicated boundary shapes, because these methods do not need to generate a grid system. In this study, a gridless solver, which is based on the combination of moving least square interpolations on a cloud of points with point collocation for evaluating the derivatives of governing equations, is presented for two-dimensional unsteady incompressible Navier-Stokes problem in the low Reynolds number. A MAC-type algorithm was adopted and the Poission equation for the pressure was solved by successively in the moving least square sense. Some weighing functions were tested in order to investigate the up-winding effect for the convection term. Some typical problems were solved by the presented solver for the validation and the results obtained were compared with analytic solutions and the numerical results by conventional CFD methods, such as FVM.

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