• Title/Summary/Keyword: least square method

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A Channel Equalization Algorithm Using Neural Network Based Data Least Squares (뉴럴네트웍에 기반한 Data Least Squares를 사용한 채널 등화기 알고리즘)

  • Lim, Jun-Seok;Pyeon, Yong-Kuk
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.2E
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    • pp.63-68
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    • 2007
  • Using the neural network model for oriented principal component analysis (OPCA), we propose a solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. In this paper, we applied this neural network model to channel equalization. Simulations show that the neural network based DLS outperforms ordinary least squares in channel equalization problems.

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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    • v.4 no.2
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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.

Experimental Study on a Monte Carlo-based Recursive Least Square Method for System Identification (몬테카를로 기반 재귀최소자승법에 의한 시스템 인식 실험 연구)

  • Lee, Sang-Deok;Jung, Seul
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.2
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    • pp.248-254
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    • 2018
  • In this paper, a Monte Carlo-based Recursive Least Square(MC-RLS) method is presented to directly identify the inverse model of the dynamical system. Although a RLS method has been used for the identification based on the deterministic data in the closed loop controlled form, it would be better for RLS to identify the model with random data. In addition, the inverse model obtained by inverting the identified forward model may not work properly. Therefore, MC-RLS can be used for the inverse model identification without proceeding a numerical inversion of an identified forward model. The performance of the proposed method is verified through experimental studies on a control moment gyroscope.

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

  • Ryu, Ki-Chan;Kang, Sang-Hee;Lee, Bong-Hyun
    • Proceedings of the KIEE Conference
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    • 2006.07a
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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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Development of an AOA Location Method Using Self-tuning Weighted Least Square (자기동조 가중최소자승법을 이용한 AOA 측위 알고리즘 개발)

  • Lee, Sung-Ho;Kim, Dong-Hyouk;Roh, Gi-Hong;Park, Kyung-Soon;Sung, Tae-Kyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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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.

Numerical analysis of three-dimensional sloshing flow using least-square and level-set method (최소자승법과 Level-set 방법을 이용한 3차원 슬로싱 유동의 수치해석)

  • Choi, Hyoung-Gwon
    • Proceedings of the KSME Conference
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    • 2008.11b
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    • pp.2401-2405
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    • 2008
  • In the present study, a three-dimensional least square/level set based two-phase flow code was developed for the simulation of three-dimensional sloshing problems using finite element discretization. The present method can be utilized for the analysis of a free surface flow problem in a complex geometry due to the feature of FEM. Since the finite element method is employed for the spatial discretization of governing equations, an unstructured mesh can be naturally adopted for the level set simulation of a free surface flow without an additional load for the code development except that solution methods of the hyperbolic type redistancing and advection equations of the level set function should be devised in order to give a bounded solution on the unstructured mesh. From the numerical experiments of the present study, it is shown that the proposed method is both robust and accurate for the simulation of three-dimensional sloshing problems.

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

  • Kim, Young-Kyoun;Kim, Sung-Il;Kwon, Soon-O;Hong, Jung-Pyo
    • Proceedings of the KIEE Conference
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    • 2003.07b
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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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A Study on Model Identification of Electro-Hydraulic Servo Systems (전기-유압 서보 시스템의 모델규명에 관한 연구)

  • 엄상오;황이철;박영산
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.4
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    • pp.907-914
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    • 1999
  • This paper studies on the model identification of electro-hydraulic servo systems, which are composed of servo valves, double-rod cylinder and load mass. The identified plant is described as a discrete-time ARX or ARMAX model which is respectively obtained from the identification algorithms of least square error method, instrumental variable method and prediction error method. where a nominal model and the variation of model parameters are quantitatively evaluated.

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Optimal Design Method for an Actively Shielded MRI Superconducting Magnet (능동 차폐 MRI 초전도 자석에 대한 최적 설계 방법)

  • Lee, Kwang-Ho;Cho, Yun-Hyun
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.49 no.6
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    • pp.421-430
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    • 2000
  • This paper describes an optimal design method which is applied a weighted least square (WLS) method for Magnetic Resonance Imaging (MRI) system. An optimal design approach is presented for a homogeneity superconducting magnet with the superconducting active shield especially for a magnetic resonance imaging system. The WLS is used to obtain the optimal configurations using the least amount and minimum volume of conductor, exhibiting the smallest level of field inhomogeneity and resulting in the least level of stray field. The proposed model is used to design a multiple-shield configuration for a 1.5 T MRI magnet. The field homogeneity is required less than 5 gauss stray field contour within 4m axially and 3m radially from origin. The designed magnet with the actively magnetic shielding coil out of main coils is analyzed by FEM and theoretical analysis method, investigated the field homogeneity.

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Estimation of Aerodynamic Coefficients for a Skid-to-Turn Missile using Neural Network and Recursive Least Square (신경회로망과 순환최소자승법을 이용한 Skid-to-Turn 미사일의 공력 파라미터 추정)

  • Kim, Yun-Hwan;Park, Kyun-Bub;Song, Yong-Kyu;Hwang, Ick-Ho;Choi, Dong-Kyun
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.20 no.4
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    • pp.7-13
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    • 2012
  • This paper is to estimate aerodynamic coefficients needed to determine the missiles' controller design and stability from simulation data of Skid-to-Turn missile. Method of determining aerodynamic coefficients is to apply Neural Network and Recursive Least Square and results were compared and researched. Also analysing actual flight test data was considered and sensor noise was added. Estimate parameter of data with sensor noise added and estimated performance and reliability for both methods that did not need initial values. Both Neural Network and Recursive Least Square methods showed excellent estimate results without adding the noise and with noise added Neural Network method showed better estimate results.