• Title/Summary/Keyword: step-size

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Kurtosis Driven Variable Step-Size Normalized Least Mean Square Algorithm for RF Repeater

  • Han, Yong-Sik;Yang, Woon-Geun
    • Journal of information and communication convergence engineering
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    • v.8 no.2
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    • pp.159-162
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    • 2010
  • This paper presents a new Kurtosis driven Variable Step-Size Normalized Least Mean Square (KVSSN-LMS) algorithm to prevent repeater from oscillation due to feedback signal of radio frequency (RF) repeater. To get better Mean Square Error (MSE) performance, step-size is adjusted using the kurtosis. The proposed algorithm shows the better performance of steady state MSE. The proposed algorithm shows a better ERLE performance than that of KVSS-LMS, VSS-NLMS, NLMS algorithms.

A LMS algorithm with variable step size (가변 스텝 크기를 갖는 LMS 알고리즘)

  • 김관준;이철희;남현도
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.224-227
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    • 1993
  • In this paper, a new LMS algorithm with a variable step size (VVS LMS) is presented. The change of step size .mu. at each iteration, which increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. The norm of the cross correlation between the estimation error and input signal is used. As a measure of the misadaptation degree. Simulation results are presented to compare the performance of the VSS LMS algorithm with the normalized LMS algorithm.

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A LMS Algorithm with Fuzzy Variable Step Size (퍼지 가변 스텝 크기 LMS 알고리즘)

  • Lee, Chul-Heu;Kim, Koan-Jun
    • Journal of Industrial Technology
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    • v.13
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    • pp.33-41
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    • 1993
  • In this paper, a new LMS algorithm with a fuzzy variable step size (FVS LMS) is presented. The change of step size ${\mu}$, at each iteration which is increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. As a measure of the misadaptation degree, the norm of the cross correlation between the estimation error and input signal is used. Simulation results are presented to compare the performance of the FVSS LMS algorithm with the normalized LMS algorithm.

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Scaling Factor Design Based Variable Step Size Incremental Resistance Maximum Power Point Tracking for PV Systems

  • Ahmed, Emad M.;Shoyama, Masahito
    • Journal of Power Electronics
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    • v.12 no.1
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    • pp.164-171
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    • 2012
  • Variable step size maximum power point trackers (MPPTs) are widely used in photovoltaic (PV) systems to extract the peak array power which depends on solar irradiation and array temperature. One essential factor which judges system dynamics and steady state performances is the scaling factor (N), which is used to update the controlling equation in the tracking algorithm to determine a new duty cycle. This paper proposes a novel stability study of variable step size incremental resistance maximum power point tracking (INR MPPT). The main contribution of this analysis appears when developing the overall small signal model of the PV system. Therefore, by using linear control theory, the boundary value of the scaling factor can be determined. The theoretical analysis and the design principle of the proposed stability analysis have been validated using MATLAB simulations, and experimentally using a fixed point digital signal processor (TMS320F2808).

Modified Asymmetrical Variable Step Size Incremental Conductance Maximum Power Point Tracking Method for Photovoltaic Systems

  • Tian, Yong;Xia, Bizhong;Xu, Zhihui;Sun, Wei
    • Journal of Power Electronics
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    • v.14 no.1
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    • pp.156-164
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    • 2014
  • The power-voltage (P-V) characteristic of a photovoltaic (PV) array is nonlinear and time varying with the change in atmospheric conditions. As a result, the maximum power point tracking (MPPT) technique must be applied in PV systems to maximize the generated energy. The incremental conductance (INC) algorithm, one of the MPPT strategies, is widely used for its high tracking accuracy, good adaptability to rapidly changing atmospheric conditions, and easy implementation. This paper presents a modified asymmetrical variable step size INC MPPT method that is based on the asymmetrical feature of the P-V curve. Compared with conventional fixed or variable step size method, the proposed method can effectively improve tracking accuracy and speed. The theoretical foundation and design principle of the proposed approach are validated by the simulation and experimental results.

An Automatic Focusing Method Using Establishment of Step Size from Optical Axis Interval (광학축 간격의 스텝크기 설정을 통한 오토포커싱 방법)

  • Kim, Gyung Bum;Moon, Soon Hwan
    • Journal of the Semiconductor & Display Technology
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    • v.14 no.1
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    • pp.7-11
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    • 2015
  • In this paper, an automatic focusing method has been proposed for speedy and reliable measurement and inspection in industry. It is very difficult to determine focusing step size and moving direction in one camera autofocusing. The proposed method can improve speed and accuracy of focusing by using the optical axis interval of two cameras, which is automatically set up as focusing step size. Also, it can determine moving direction from focus value comparisons of two cameras, and then solve ambiguity of one camera focusing. Its performance is verified by experiments. It is expected that it can apply to optical system for measurement and inspection in industry fields.

Blind Source Separation U sing Variable Step-Size Adaptive Algorithm in Frequency Domain

  • Park Keun-Soo;Lee Kwang-Jae;Park Jang-Sik;Son Kyung Sik
    • Journal of Korea Multimedia Society
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    • v.8 no.6
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    • pp.753-760
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    • 2005
  • This paper introduces a variable step-size adaptive algorithm for blind source separation. From the frequency characteristics of mixed input signals, we need to adjust the convergence speed regularly in each frequency bin. This algorithm varies a step-size according to the magnitude of input at each frequency bin. This guarantee of the regular convergence in each frequency bin would become more efficient in separation performances than conventional fixed step-size FDICA. Computer simulation results show the improvement of about 5 dB in signal to interference ratio (SIR) and the better separation quality.

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Performance Evaluation of a Dual-Mode Blind Equalization Algorithm Using the Size of Decision-Directed Error Signal for High-Order QAM Signals (고차 QAM 신호에 대한 결정 지향 오차 신호의 크기 값을 이용한 이중 모드 블라인드 등화 알고리즘의 성능 분석)

  • Jeong, Young-Hwa
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.3
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    • pp.89-95
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    • 2016
  • In this paper, we propose a dual-mode blind equalization algorithm that two of the blind equalization algorithm using the size of the decision-directed error signal is automatically switched. The proposed algorithm has a faster convergence speed due to operation of the MSAGF-SMMA with large fixed step-size mainly in the initial equalization. After the equalization has been made to some extent, the proposed algorithm has a smaller residual error in the steady- state by operation of the MSAGF-SMMA with a variable step-size mainly. The variable step-size is determined by multiplying the size of the decision-directed error signal of a fixed step-size. In this paper, we analyze the performance of the proposed algorithm. The computer simulation results demonstrate that the proposed algorithm has a significantly improved performance in terms of a residual inter-symbol interference and residual error in the steady-state compared with the MMA, SMMA, and MSAGF-SMMA.

Novel Variable Step-Size Gradient Adaptive Lattice Algorithm for Active Noise Control (능동 소음 제어를 위한 새로운 가변 수렴 상수 Gradient Adaptive Lattice Algorithm)

  • Lee, Keunsang;Kim, Seong-Woo;Im, Jaepoong;Seo, Young-Soo;Park, Youngcheol
    • The Journal of the Acoustical Society of Korea
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    • v.33 no.5
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    • pp.309-315
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    • 2014
  • In this paper, a novel variable step-size filtered-x gradient adaptive lattice (NVSS-FxGAL) algorithm for active noise control system is proposed. The gradient adaptive lattice (GAL) algorithm is capable of controlling the narrow band noise effectively. The GAL algorithm can achieve both fast convergence rate and low steady-state level using the variable step-size. However, it suffers from the convergence performance for varying signal characteristic since the global variable step-size is equally applied to all lattice stages. Therefore, the proposed algorithm guarantees the stable and consistency convergence performance by using the local variable step-size for the suitable each lattice stage. Simulation results confirm that the proposed algorithm can obtain the fast convergence rate and low steady-state level compared to the conventional algorithms.

A Prediction Method using Markov chain for Step Size Control in FMI based Co-simulation (FMI기반 co-simulation에서 step size control을 위한 Markov chain을 사용한 예측 방법)

  • Hong, Seokjoon;Lim, Ducsun;Kim, Wontae;Joe, Inwhee
    • Journal of IKEEE
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    • v.23 no.4
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    • pp.1430-1439
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    • 2019
  • In Functional Mockup Interface(FMI)-based co-simulation, a bisectional algorithm can be used to find the zerocrossing point as a way to improve the accuracy of the simulation results. In this paper, the proposed master algorithm(MA) analyzes the repeated interval graph and predicts the next interval by applying the Markov Chain to the step size. In the simulation, we propose an algorithm to minimize the rollback by storing the step size that changes according to the graph type as an array and applying it to the next prediction interval when the rollback occurs in the simulation. Simulation results show that the proposed algorithm reduces the simulation time by more than 20% compared to the existing algorithm.