• 제목/요약/키워드: Least Square Problem

검색결과 251건 처리시간 0.025초

TDOA 측정치를 이용한 가중치 추정방식의 QCLS 측위 방법 (An Efficient QCLS Positioning Method Using Weight Estimation for TDOA Measurements)

  • 김동혁;송승헌;박경순;성태경
    • 전자공학회논문지SC
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    • 제44권4호통권316호
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    • pp.1-7
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    • 2007
  • 지상파 측위와 같이 사용자와 센서간의 거리가 짧은 경우에는 GN (Gauss-Newton) 방법을 이용하여 구한 추정치가 발산하기도 한다. 이러한 문제점을 해결하기 위하여 TDOA (Time Difference of Arrival) 측정치에 대해서는 QCLS (Quadratic Correction Least Square) 방법이 개발되었으나 추정치의 오차가 다소 크다는 문제점을 보였다. 본 논문에서는 가중최소자승법을 도입하여 기존 QCLS 방법의 성능을 개선하는 방안을 제안하였다. 제안한 방법에서 사용하는 가중행렬이 미지변수인 사용자 위치의 함수이기 때문에 먼저 가중행렬의 추정치를 구한 후 이를 이용하여 사용자 위치 추정치를 구하는 단계별 추정 방식을 제안하였다. 컴퓨터 시뮬레이션을 통하여 제안한 방법의 성능이 기존 QCLS 방법보다 항상 우수함을 보였으며, Gauss-Newton 방법이 수렴하는 경우 두 가지 방법이 대등한 성능을 보였다.

MODIFIED GEOMETRIC PROGRAMMING PROBLEM AND ITS APPLICATIONS

  • ISLAM SAHIDUL;KUMAR ROY TAPAN
    • Journal of applied mathematics & informatics
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    • 제17권1_2_3호
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    • pp.121-144
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    • 2005
  • In this paper, we propose unconstrained and constrained posynomial Geometric Programming (GP) problem with negative or positive integral degree of difficulty. Conventional GP approach has been modified to solve some special type of GP problems. In specific case, when the degree of difficulty is negative, the normality and the orthogonality conditions of the dual program give a system of linear equations. No general solution vector exists for this system of linear equations. But an approximate solution can be determined by the least square and also max-min method. Here, modified form of geometric programming method has been demonstrated and for that purpose necessary theorems have been derived. Finally, these are illustrated by numerical examples and applications.

ADMM for least square problems with pairwise-difference penalties for coefficient grouping

  • Park, Soohee;Shin, Seung Jun
    • Communications for Statistical Applications and Methods
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    • 제29권4호
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    • pp.441-451
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    • 2022
  • In the era of bigdata, scalability is a crucial issue in learning models. Among many others, the Alternating Direction of Multipliers (ADMM, Boyd et al., 2011) algorithm has gained great popularity in solving large-scale problems efficiently. In this article, we propose applying the ADMM algorithm to solve the least square problem penalized by the pairwise-difference penalty, frequently used to identify group structures among coefficients. ADMM algorithm enables us to solve the high-dimensional problem efficiently in a unified fashion and thus allows us to employ several different types of penalty functions such as LASSO, Elastic Net, SCAD, and MCP for the penalized problem. Additionally, the ADMM algorithm naturally extends the algorithm to distributed computation and real-time updates, both desirable when dealing with large amounts of data.

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.

Analysis of a Gas Circuit Breaker Using the Fast Moving Least Square Reproducing Kernel Method

  • Lee, Chany;Kim, Do-Wan;Park, Sang-Hun;Kim, Hong-Kyu;Jung, Hyun-Kyo
    • Journal of Electrical Engineering and Technology
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    • 제4권2호
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    • pp.272-276
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    • 2009
  • In this paper, the arc region of a gas circuit breaker (GCB) is analyzed using the fast moving least square reproducing kernel method (FMLSRKM) which can simultaneously calculate an approximated solution and its derivatives. For this problem, an axisymmetric and inhomogeneous formulation of the FMLSRKM is used and applied. The field distribution obtained by the FMLSRKM is compared to that of the finite element method. Then, a whole breaking period of a GCB is simulated, including analysis of the arc gas flow by finite volume fluid in the cell, and the electric field of the arc region using the FMLSRKM.

내삽법 기반의 최소자승법을 이용한 개선된 CT 포화 복원 알고리즘 (An Enhanced Compensation Algorithm for the CT Saturation Using Interpolation-based LSQ(Least Square) Fitting Method)

  • 류기찬;강상희;이봉현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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    • pp.14-15
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    • 2006
  • A saturation of magnetic flux in the core may occur when a large primary current flows when the iron-cored current transformer is used. This saturation makes the distorted secondary current of the CT. the distorted secondary current may cause the mal-operation or operation time delay of protective relays. CT compensation algorithm using The LSQ(Least Square) fitting method has a problem. It needs to acquire enough data for executing this algorithm without an error. In this paper, an enhanced algorithm using interpolation based LSQ(Least Square) Fitting Method is proposed. The Lagrange Interpolation Method is used for the interpolation and CT is simulated by EMTP. The results show that the proposed algorithm can accurately compensate a distorted secondary current more than existing Algorithm when the saturation severely occurs.

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자기동조 가중최소자승법을 이용한 AOA 측위 알고리즘 개발 (Development of an AOA Location Method Using Self-tuning Weighted Least Square)

  • 이성호;김동혁;노기홍;박경순;성태경
    • 제어로봇시스템학회논문지
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    • 제13권7호
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    • pp.683-687
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    • 2007
  • In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and Closed-Form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-Form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a Self-Tuning Weighted Least Square AOA algorithm that is a modified version of the conventional Closed-Form solution. In order to estimate the error covariance matrix as a weight, a two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

이동최소자승법을 이용한 선형동기전동기의 디텐트력 특성 예측 (Prediction of Detent Force on Linear Synchronous Motor by means of Moving Least Square Method)

  • 김영균;김성일;권순오;홍정표
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 B
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    • pp.994-996
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    • 2003
  • The Response Surface Methodology is frequently used for building an approximation model. However, its approximation errors often occur in engineering problem, because of the use of the Least Square Method. Therefore, this paper introduces the Moving Least Square Method to obtain the more accurate Response Surface Model, and then the detent force of a Permanent Magnet Linear Synchronous Motor is applied to verify the accuracy of the introduced method.

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도로포장 반응모형에 대한 통계모형 개발 (A Development of Statistical Model for Pavement Response Model)

  • 이문섭;박희문;김부일;허태영
    • 한국산업정보학회논문지
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    • 제17권5호
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    • pp.89-96
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    • 2012
  • 도로포장 반응모형의 구축을 위하여 새로운 방법론으로 부분최소제곱회귀모형의 활용성을 소개하고 실제 FWD 실험자료에 적용시켰다. 실증분석 결과 일반 다중회귀모형에서 발생된 다중공선성 문제를 부분최소제곱회귀모형을 통하여 해결방안을 제시하였으며, 변환된 자료가 아닌 원시자료를 이용하여 모형을 구축할 수 있다는 장점도 가지고 있다.

Parallel Implementation of the Recursive Least Square for Hyperspectral Image Compression on GPUs

  • Li, Changguo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권7호
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    • pp.3543-3557
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    • 2017
  • Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.