• Title/Summary/Keyword: A least square error

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Optimal Grayscale Morphological Filters Under the LMS Criterion (LMS 알고리즘을 이용한 형태학 필터의 최적화 방안에 관한 연구)

  • 이경훈;고성제
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.6
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    • pp.1095-1106
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    • 1994
  • This paper presents a method for determining optimal grayscale function processing(FP) morphological filters under the least square (LMS) error criterion. The optimal erosion and dilation filters with a grayscale structuring element(GSE) are determined by minimizing the mean square error (MSE) between the desired signal and the filter output. It is shown that convergence of the erosion and dilation filters can be achieved by a proper choice of the step size parameter of the LMS algorithm. In an attempt to determine optimal closing and opening filters, a matrix representation of both opening and closing with a basis matrix is proposed. With this representation, opening and closing are accomplished by a local matrix operation rather than cascade operations. The LMS and back-propagation algorithm are utilzed for obtaining the optimal basis matrix for closing and opening. Some results of optimal morphological filters applied to 2-D images are presented.

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Compensation Method of Position Signal Error with Misaligned Hall-Effect Sensors of BLDC Motor

  • Park, Joon Sung;Choi, Jun-Hyuk;Lee, Ju
    • Journal of Electrical Engineering and Technology
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    • v.11 no.4
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    • pp.889-897
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    • 2016
  • This paper presents an improved approach for compensating rotor position signal displacement in brushless DC (BLDC) motors with misaligned hall-effect sensors. Typically, the hall-effect sensors in BLDC motors are located in each phase and positioned exactly 120 electrical degrees apart. However, limitations in mechanical tolerances make it difficult to place hall-effect sensors at the correct location. In this paper, a position error compensator to counteract the hall-effect sensor positioning error is proposed. The proposed position error compensator uses least squares error analysis to adjust the relative position error and back-EMF information to reduce the absolute offset error. The effectiveness of the proposed approach is verified through several experiments.

A Comparison of Estimation Methods for Weibull Distribution and Type I Censoring (와이블 분포와 정시중단 하에서의 MLE와 LSE의 정확도 비교)

  • Kim, Seong-Il;Park, Min-Yong;Park, Jung-Won
    • Journal of Korean Society for Quality Management
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    • v.38 no.4
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    • pp.480-490
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    • 2010
  • In this paper, two estimation methods(least square estimation and maximum likelihood estimation) were compared for Weibull distribution and Type I censoring. Data obtained by Monte Carlo simulation were analyzed using two estimation methods and analysis results were compared by MSE(Mean Squared Error). Comparison results show that maximum likelihood estimator is better for censored data and complete data with more than 30 samples and least square estimator is better for small size complete data(less than and equal to 20 samples).

A Note on Disturbance Variance Estimator in Panel Data with Equicorrelated Error Components

  • Seuck Heun Song
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.129-134
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    • 1995
  • The ordinary least square estimator of the disturbance variance in the pooled cross-sectional and time series regression model is shown to be asymptotically unbiased without any restrictions on the regressor matrix when the disturbances follow an equicorrelated error component models.

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Accelerometer Signal Processing for a Helicopter Active Vibration Control System (헬리콥터 능동진동제어시스템 가속도 신호 처리)

  • Kim, Do-Hyung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.45 no.10
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    • pp.863-871
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    • 2017
  • LMS (least mean square) algorithm widely used in the AVCS (active vibration control system) of helicopters calculates control input using the forward path transfer function and error signal. If the error signal is sinusoidal, it can be represented as the combination of cosine and sine functions with frequency and phase synchronized with the reference signal. The control input also has the same frequency, therefore control algorithm can be simply implemented if the cosine and the sine amplitudes of the control input are calculated and the frequency and phase of the reference signal are used. Calculation of the control input is implemented as simple matrix operation and the change of the control command is slower than the frequency of the error signal, consequently control algorithm can be operated at lower frequency. The signal processing algorithm extracting cosine and sine components of the error signals are modeled using Simulink and PIL (processor-in-the-loop) mode simulation was executed for real-time performance evaluation.

Doppler-shift estimation of flat underwater channel using data-aided least-square approach

  • Pan, Weiqiang;Liu, Ping;Chen, Fangjiong;Ji, Fei;Feng, Jing
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.7 no.2
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    • pp.426-434
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    • 2015
  • In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB) of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.

An improved sparsity-aware normalized least-mean-square scheme for underwater communication

  • Anand, Kumar;Prashant Kumar
    • ETRI Journal
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    • v.45 no.3
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    • pp.379-393
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    • 2023
  • Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l1-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

An error- diffusion halftoning technique based on noise spectrum shaping (잡음주파수특성 성형에 의한 오차확산 영상이진화 기법)

  • 이광기;이재천;권용무;김형곤
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.11
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    • pp.1464-1472
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    • 1995
  • In this paper, we propose an error diffusion image halftoning technique based on the noise spectrum shaping. The new technique can arbitrarily control the shape of the display error spectrum whereas conventional halftoning algorithms have been known to minimize dc errors only in which case edge information cannot be properly rendered. As a method for estimating the error diffusion coefficients, a least mean square (LMS) approach is adopted.

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Modeling and Parameter Estimation of Solenoid Valve in Automatic Transmission by the Least Square Method (최소자승법에 의한 A/T용 솔레노이드 밸브의 모델링 및 파라미터 평가)

  • 노형우;박상훈;송창섭
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.10
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    • pp.98-104
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    • 2003
  • Model structure of solenoid valve in the automatic transmission is determined as 5th order system by the signal error test. For determining parameter of the solenoid valve, parameters in time discrete model are searched by the least square method. By bilinear transform, we have found the model of solenoid valve in s domain. Afterward, experimental output data is compared with simulated output data by MATLAB having identified parameter. As the result, experimental data is agreed with simulated data very well.

Geometrical Compensation of Injection-Molded Thin-Walled Parts in Reverse Engineering

  • Kim Yeun Sul;Lee Hi Koan;Huang Jing Chung;Kong Young Sik;Yang Gyun Eui
    • International Journal of Precision Engineering and Manufacturing
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    • v.6 no.2
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    • pp.12-18
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    • 2005
  • A geometric compensation of thin-walled molded parts in reverse engineering is presented. Researches in reverse engineering have focused on the fitting of points to curves and surfaces. However, the reconstructed model is not the geometric model because the molded parts have some dimensional errors in measurements and deformation during molding. Geometric information can give an improved accuracy in reverse engineering. Thus, measurement data must be compensated with geometric information to reconstruct the mathematical model. The functional and geometric concepts of the part can be derived from geometric information. LSM (Least square method) is adopted to determine the geometric information. Also, an example of geometric compensation is given to improve the accuracy of geometric model and to inspect the reconstructed model.