• Title/Summary/Keyword: Least Squares Algorithm

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Precise Edge Detection Method Using Sigmoid Function in Blurry and Noisy Image for TFT-LCD 2D Critical Dimension Measurement

  • Lee, Seung Woo;Lee, Sin Yong;Pahk, Heui Jae
    • Current Optics and Photonics
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    • v.2 no.1
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    • pp.69-78
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    • 2018
  • This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

Intelligent Parameter Estimation of a Induction Motor Using Immune Algorithm

  • Kim, Dong-Hwa;Cho, Jae-Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.21-25
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    • 2004
  • This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase squirrel-cage induction machine using immune algorithm. The parameter estimation procedure is based on the steady state phase current versus slip and input power versus slip characteristics. The proposed estimation algorithm is of a nonlinear kind based on clonal selection in immune algorithm. The machine parameters are obtained as the solution of a minimization of least-squares cost function by immune algorithm. Simulation shows better results than the conventional approaches.

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Numerical Algorithm for Distance Protection and Arcing Fault Recognitior (고장거리계산과 아크고장 판별 알고리즘)

  • Radojevic, Zoran;Park, K.W.;Park, J.S.
    • Proceedings of the KIEE Conference
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    • 2002.07a
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    • pp.163-165
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    • 2002
  • In this paper a new numerical algorithm for fault distance calculation and arcing fault recognition based on one terminal data and derived in lime domain is presented. The algorithm is derived for the case of most frequent single-phase line to ground fault. The faulted phase voltage at the fault place is modeled as a serial connection of fault resistance and arc voltage. The fault distance and arc voltage amplitude are estimated using Least Error Squares Technique. The algorithm can be applied for distance protection, intelligent autoreclosure and for fault location. The results of algorithm tested through computer simulation are given.

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Novel Digital Cancelation Method in Presence of Harmonic Self-Interference

  • Ju, Hyungsik;Gwak, Donghyuk;Lee, Yuro;Kim, Tae-Joong
    • ETRI Journal
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    • v.39 no.2
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    • pp.245-254
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    • 2017
  • In-band full-duplex (IFD) communication has recently attracted a great deal of interest because it potentially provides a two-fold spectral efficiency increase over half-duplex communications. In this paper, we propose a novel digital self-interference cancelation (DSIC) algorithm for an IFD communication system in which two nodes exchange orthogonal frequency-division multiplexing (OFDM) symbols. The proposed DSIC algorithm is based on the least-squares estimation of a self-interference (SI) channel with block processing of multiple OFDM symbols, in order to eliminate the fundamental and harmonic components of SI induced through the practical radio frequency devices of an IFD transceiver. In addition, the proposed DSIC algorithm adopts discrete Fourier transform processing of the estimated SI channel to further enhance its cancelation performance. We provide a minimum number of training symbols to estimate the SI channel effectively. The evaluation results show that our proposed DSIC algorithm outperforms a conventional algorithm.

A study on the design of adaptive generalized predictive control (적응 일반형 예측제어 설계에 관한 연구)

  • 김창회;이상정
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.176-181
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    • 1992
  • In this paper, an adaptive generalized predictive control(GPC) algorithm which minimizes a N-stage cost function is proposed. The resulting controller is based on GPC algorithm and can be used in unknown plant parameters as the parameters of one step ahead predictor are estimated by recursive least squares method. The estimated parameters are extended to G,P, and F amtrix which contain the parameters of N step ahead predictors. And the minimization of cost function assuming no constraints on future controls results in the projected control increment vector. Hence this adaptive GPC algorithm can be used for either unknown system or varing system parameters, and it is also shown through simulations that the algorithm is robust to the variation of system parameters. This adaptive GPC scheme is shown to have the same stability properties as the deterministic GPC, and requires small amount of calculation compared to other adaptive algorithms which minimize N-stage cost function. Especially, in case that the maximum output horizon is 1, the proposed algorithm can be applicable to direct adaptive GPC.

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Complex Fuzzy Logic Filter and Learning Algorithm

  • Lee, Ki-Yong;Lee, Joo-Hum
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.1E
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    • pp.36-43
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    • 1998
  • A fuzzy logic filter is constructed from a set of fuzzy IF-THEN rules which change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy logic filter and it's adaptive filtering algorithm to include complex parameters and complex signals. Using the complex Stone-Weierstrass theorem, we prove that linear combinations of the fuzzy basis functions are capable of uniformly approximating and complex continuous function on a compact set to arbitrary accuracy. Based on the fuzzy basis function representations, a complex orthogonal least-squares (COLS) learning algorithm is developed for designing fuzzy systems based on given input-output pairs. Also, we propose an adaptive algorithm based on LMS which adjust simultaneously filter parameters and the parameter of the membership function which characterize the fuzzy concepts in the IF-THEN rules. The modeling of a nonlinear communications channel based on a complex fuzzy is used to demonstrate the effectiveness of these algorithm.

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Development of A New Patch-Based Stereo Matching Algorithm for Extraction of Digiral Elevation Model from Satellite Imagery (위성영상으로부터 수치표고모형 추출을 위한 새로운 정합구역의 비선형 최소자승 영상정합 알고리즘 개발)

  • 김태정;이흥규
    • Korean Journal of Remote Sensing
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    • v.13 no.2
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    • pp.121-132
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    • 1997
  • This paper describes the development of a stereo matching algorithm for extracting Digital Elevation Model(DEM) from satellite images. This matching algorithm is based on a non-linear least squares correlation estimation but has improved matching speed. The algorithm consists of three steps: matching execution, matching control and matching optimization. Each is described. The performance of the presented algorithm is quantitatively analyzed with experiments on matching probability, matching speed and matching convergence radius.

이송 물체의 질량 측정 속도 향상

  • 이우갑;정진완;김광표
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.328-332
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    • 1993
  • This study presents an algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is applied for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined form the step input. The performance of the algorithm was tested on a check weigher. Discussions were extended to the development of noise reduction techniques and to the lagged introduction of objects on the moving plate. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted real-time signal processing, which are high precision and stability in noisy environment.

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Development of Job Satisfaction Measurement Model Using Structural Equation Model (구조방정식모델을 이용한 직무만족도 평가모형 개발)

  • Chun, Young-Ho
    • Journal of Korean Society for Quality Management
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    • v.39 no.1
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    • pp.90-97
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    • 2011
  • The purpose of this study is to analyze various factors comprising a job satisfaction; determine possible factors that affects job satisfaction. Job satisfaction model is designed to evaluate major factors, such as job stress and strength, and to assess relationship between these factors. Partial least squares algorithm is used to develop a job satisfaction measurement model. To evaluate validity of developed model, survey data of health insurance review and assessment service is to applied.

Sliding Mode Observer (SMO) using Aging Compensation based State-of-Charge(SOC) Estimation for Li-Ion Battery Pack

  • Kim, Jonghoon;Nikitenkov, Dmitry;Denisova, Valeria
    • Proceedings of the KIPE Conference
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    • 2013.11a
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    • pp.200-201
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    • 2013
  • This paper investigates a new approach for Li-Ion battery state-of-charge (SOC) estimation using sliding mode observer (SMO) technique including parameters aging compensation via recursive least squares (RLS). The main advantages of this approach would be low computational load, easiness of implementation along with the robustness of the method for internal battery model parameters estimation. The proposed algorithm was first tested on a set of acquired battery data using implementation in Simulink and later developed as C-code module for firmware application.

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