• Title/Summary/Keyword: least square algorithm

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Design and Implementation of IIR Multiple Notch Filter with Modified Pole-Zero Placement Algorithm

  • Yimman, Surapun;Hinjit, Watcharapong;Ussawongaraya, Weerasak;Thoopluang, Payao;Dejhan, Kobchai
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.65-68
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    • 2003
  • This paper presents a design and construction of IIR multiple notch filter by modifying the pole-zero placement with least square estimation to find the appropriate gain and pole positions for the filter within a unit circle in z-plane. The appropriated gain and pole position will render the controllable unit gain of filter magnitude. Algorithm design and system simulation are performed on MATLAB while the actual implementation is done on the TMS320C31 digital signal processing board.

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Estimation of Rotation Center and Rotation Angle for Real-time Image Stabilization of Roll Axis. (실시간 회전영상 안정화를 위한 회전중심 및 회전각도 추정 방법)

  • Cho, Jae-Soo;Kim, Do-Jong
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.153-155
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    • 2004
  • This paper proposes a real-time approach on the rotational motion estimation and correction for the roll stabilization of the sight system. This method first estimates a rotation center by the least-mean square algorithm based on the motion vectors of some feature points. And, then, a rotation angle is searched for a best matching block between a reference block image and seccessive input images using MPC(maximum pixel count) matching criterion. Finally, motion correction is performed by the bilinear interpolation technique. Various computer simulations show that the estimation performance is good and the proposed algorithm is a real-time implementable one to the TMS320C6415(500MHz) DSP.

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A Neural Multiple LMS Based ANC System for Reducing Acoustic Noise of High-Speed Trains (신경회로망 다중 LMS 기법을 이용한 고속철도의 실내소음저감을 위한 ANC 시스템)

  • Cho, Hyun-Cheol;Lee, Kwon-Soon;Nam, Hyun-Do
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.58 no.4
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    • pp.385-390
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    • 2009
  • This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

Application SVD-Least Square Algorithm for solving astronomical ship position basing on circle of equal altitude equation

  • Nguyen, Van Suong;Im, Namkyun
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2013.10a
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    • pp.130-132
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    • 2013
  • This paper presents an improvement for calculating method of astronomical vessel position with circle of equal altitude equation based on using a virtual object in sun and two stars observation. In addition, to enhance the accuracy of ship position achieved from solving linear matrix system, and surmount the disadvantages on rank deficient matrices situation, the authors used singular value decomposition (SVD) in least square method instead of normal equation and QR decomposition, so, the solution of matrix system will be available in all situation. As proposal algorithm, astronomical ship position will give more accuracy than previous methods.

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Inertia and Coefficient of Friction Estimation of Electric Motor using Recursive Least-Mean-Square Method (순환 최소자승법을 이용한 전동기 관성과 마찰계수 추정)

  • Kim, Ji-Hye;Choi, Jong-Woo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.2
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    • pp.311-316
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    • 2007
  • This paper proposes the algorithm which estimates moment of the inertia and friction coefficient of friction for high performance speed control of electric motor. The proposed algorithm finds the moment of inertia and friction coefficient of friction by observing the speed error signal generated by the speed observer and using Recursive Least-Mean-Square method(RLS). By feedbacking the estimated inertia and estimated coefficient of friction to speed controller and full order speed observer, then the errors of the inertia and coefficient of friction and speed due to the inaccurate initial value are decreased. Inertia and coefficient of friction converge to the actual value within several times of speed changing. Simulation and actual experiment results are given to demonstrate the effectiveness of the proposed parameter estimator.

Hearing aid application of feedback cancellation algorithm in frequency domain (주파수 대역에서의 피드백 제거 알고리즘의 보청기 응용)

  • Jarng, Soon-Suck
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.4
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    • pp.272-279
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    • 2016
  • In this paper, the realization of a hearing aid adaptively cancelling feedback noise was considered. Conventional least mean square method in time domain was transformed into frequency domain in order to minimize computational burden. The adaptive filter algorithm was evaluated by Matlab (Matrix laboratory), and it was confirmed by CSR 8675 Bluetooth DSP IC (Digital Signal Processor Integrated Circuit) chip firmware realization. Some remote control features by a smart phone was added to the smart hearing aid for user interface easiness.

A Study on Development of Algorithm for Predicting the Optimized Process Parameters on Bead Geometry (임의의 비드형상을 의한 최적의 공정변수 예측 알고리즘 개발에 관한 연구)

  • 김일수;차용훈;이연신;박창언;손준식
    • Journal of Welding and Joining
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    • v.17 no.4
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    • pp.39-45
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    • 1999
  • The procedure of robotic Gas metal Arc (GMA) welding in order to achieve the optimized bead geometry needs the selection of suitable process parameters such as arc current, welding voltage, welding speed. It is required the relationships between process parameters and bead geometry. The objective of this paper is to develop the algorithm that enables the determination of process parameters from the optimized bead geometry for robotic GMA welding. It depends on the inversion of empirical equations derived from multiple regression analysis of the relationships between the process parameters and the bead dimensions using the least square method. The method not only directly determines those parameters which will give the desired set of bead geometry, but also avoids the need to iterate with a succession of guesses employed Finite Element Method(FEM). These results suggest that process parameter from experimental equation for robotic GMA welding may be employed to monitor and control the bead geometry in real time.

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Development of the Emotion Evaluation System for the Repeated Computational Stress (반복 연산 스트레스에 대한 감성 평가 시스템 구현)

  • 박광훈;하은호;김동윤;김승태;김동선
    • Journal of Biomedical Engineering Research
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    • v.22 no.1
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    • pp.19-27
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    • 2001
  • 본 연구에서는 20대 남자 대학생 45명에게 반복 연산 스트레스를 유발시키기 위하여 세 단계의 난이도를 갖는 덧셈 연산을 수행하게 하였으며, 이때 각 피검자들로부터 이에 대한 생체 신호를 측정하였다. 측정된 생체 신호로부터 제시된 연산 스트레스에 대한 감성을 평가하기 위하여 7개의 생체 파라미터를 사용하였고, 비선형 특성을 갖는 연산 스트레스에 대한 감성을 평가하기 위하여 세 단계의 구조를 갖는 감성 평가 시스템을 구성하였다. 또한 감성평가 시스템의 성능을 비교하기 위하여 평가 시스템의 각 단계를 선형 판별 알고리즘인 Least Mean Square Algorithm을 이용한 경우와 비선형 판별 알고리즘인 Radial-Based Functional-link Net을 이용한 경우를 사용하였다. 각 감성 평가 시스템은 Cross Validation을 사용하여 성능을 비교하였으며, 전체 감성 평가 시스템에서의 연산 스트레스에 대한 감성 평가 정확도는 선형 알고리즘을 이용할 경우 63.02%, RBFLN을 이용한 경우는 83.07%를 얻었다.

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Intelligent fuzzy weighted input estimation method for the input force on the plate structure

  • Lee, Ming-Hui;Chen, Tsung-Chien
    • Structural Engineering and Mechanics
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    • v.34 no.1
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    • pp.1-14
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    • 2010
  • The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

Parameter Estimation of Two-mass System using Adaptive System and Acceleration Information. (적응시스템과 가속도정보를 이용한 이관성 시스템의 기계계 파라미터 추정)

  • 이준호
    • Proceedings of the KIPE Conference
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    • 2000.07a
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    • pp.232-236
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    • 2000
  • In this paper a novel estimation algorithm of mechanical parameters in two-mass system is proposed. The inertia of a load and a motor and the stiffness are estimated by using RLS (Recursive Least Square) algorithm and acceleration information of motor. The effectiveness of the proposed scheme is verified with simulation and experiments results.

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