The paper presents art adaptive least mean squares (lms) algorithm for the fast estimation of voltage and current signals in power networks. The new estimator is based on the use of linear combiners. The learning para...
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The paper presents art adaptive least mean squares (lms) algorithm for the fast estimation of voltage and current signals in power networks. The new estimator is based on the use of linear combiners. The learning parameter of the proposed algorithm is constrained by two variable parameters which causes an automatic suitable adjustment of the step size using a fuzzy gain scheduling method to provide fast convergence and noise rejection for the tracking of fundamental and harmonic components from distorted signals. Several numerical tests have been conducted for the adaptive estimation of fundamental and harmonic components from simulated waveforms from power networks supplying converter loads and switched capacitors. (C) 1998 Published by Elsevier Science Ltd All rights reserved.
lms algorithm floating point arithmetic in hardware implementation system takes up more resources, hardware running slow and can not meet the real-time requirements of the system. So we need fixed-point arithmetic for...
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ISBN:
(纸本)9781467394451
lms algorithm floating point arithmetic in hardware implementation system takes up more resources, hardware running slow and can not meet the real-time requirements of the system. So we need fixed-point arithmetic for lms algorithm. Doing algorithm modeling with System Generator in Simulink environment will be implement in ISE and MATLAB. We can make adjustments and do the corresponding design and simulation for fixed-point methods. Simulation results show that fixed-point arithmetic module can cellation noise well. But compared with floating-point arithmetic modules, there are a little errors. lms algorithm module can achieve lms algorithm effectively. In the Simulink environment, it lay a good foundation for complex system fixed-point implementation.
This paper studies the stochastic behavior of the lms algorithm for a system identification framework when the input signal is a cyclostationary colored Gaussian process. The unknown system is modeled by the standard ...
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This paper studies the stochastic behavior of the lms algorithm for a system identification framework when the input signal is a cyclostationary colored Gaussian process. The unknown system is modeled by the standard random walk model. Well-known results for the lms algorithm are extended to the cyclostationary case and used for predicting the mean-square weight deviation (MSD) and excess meansquare error (EMSE) behavior of the algorithm. Monte Carlo simulations provide strong support for the theory. (C) 2019 Elsevier B.V. All rights reserved.
An exact analysis is presented for the lms algorithm with tonal reference signals in the presence of frequency mismatch. First, the time-varying linear system describing the lms algorithm is converted into a time-inva...
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An exact analysis is presented for the lms algorithm with tonal reference signals in the presence of frequency mismatch. First, the time-varying linear system describing the lms algorithm is converted into a time-invariant linear system. Then, a necessary and sufficient condition about the step sizes for convergence of the algorithm is derived using the Lyapunov function method and a transient behavior is analyzed. Finally, the effects of observation noise and frequency mismatch are examined without any approximations. The validity of the obtained results is shown by simulations. (c) 2005 Elsevier B.V. All rights reserved.
This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-lms) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly ...
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This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-lms) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh distributed tap coefficients. The multiuser channel estimator based on minimum-mean-square-error (MMSE) criterion is used to predict the filter coefficients. We also present its convergence characteristics and tracking performance using the RK-lms algorithm. Unlike the previously available Kalman filtering algorithm based approach (Chen, Chen IEEE Trans Signal Process 49(7): 1523-1532, 2001) the incorporation of RK-lms algorithm reduces the computational complexity of multiuser channel estimator used in the code division multiple access wireless systems. The computer simulation results are presented to demonstrate the substantial improvement in its tracking performance under the smoothly time-varying environment.
Background: A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an lms algorithm ut...
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Background: A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an lms algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE). Method: Equations for normalization of x-axis and y-axis shift and scale are first derived. The algorithm is implemented for real-time analysis of CFAE acquired during atrial fibrillation (AF). Data was acquired at a 977 Hz sampling rate from 10 paroxysmal and 10 persistent AF patients undergoing clinical electrophysiologic study and catheter ablation therapy. Over 24 trials, normalization characteristics using the new algorithm with four weights were compared to the Widrow-Hoff lms algorithm with four tapped delays. The time for convergence, and the mean squared error (MSE) after convergence, were compared. The new lms algorithm was also applied to lead aVF of the electrocardiogram in one patient with longstanding persistent AF, to enhance the F wave and to monitor extrinsic changes in signal shape. The average waveform over a 25 s interval was used as a prototypical reference signal for matching with the aVF lead. Results: Based on the derivation equations, the y-shift and y-scale adjustments of the new lms algorithm were shown to be equivalent to the scalar form of the Widrow-Hoff lms algorithm. For x-shift and x-scale adjustments, rather than implementing a long tapped delay as in Widrow-Hoff lms, the new method uses only two weights. After convergence, the MSE for matching paroxysmal CFAE averaged 0.46 +/- 0.49 mu V-2/sample for the new lms algorithm versus 0.72 +/- 0.35 mu V-2/sample for Widrow-Hoff lms. The MSE for matching persistent CFAE averaged 0.55 +/- 0.95 mu V-2/sample for the new lms algorithm versus 0.62 +/- 0.55 mu V-2/sample for Widrow-Hoff lms. There were no signific
In this article, an adaptive semi-active SSDV (Synchronized Switch Damping on Voltage) method based on the lms algorithm is proposed and applied to the vibration control of a composite beam. In the SSDV method, the va...
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In this article, an adaptive semi-active SSDV (Synchronized Switch Damping on Voltage) method based on the lms algorithm is proposed and applied to the vibration control of a composite beam. In the SSDV method, the value of voltage source in the switching circuit is critical to its control performance. In the adaptive approach proposed in this study, the voltage source is adjusted adaptively using the lms algorithm. Two cases of the adjustment are considered. In the first case, as an improvement to the enhanced SSDV, the voltage coefficient is adjusted by the lms algorithm. In the second case, as an improvement to the classical SSDV, the voltage value is adjusted directly. The new adaptive approach is compared with the derivative-based adaptive SSDV proposed in the former study in the control of the first mode of a composite beam. The control results show that adaptive adjustment of voltage value and adaptive adjustment of voltage coefficient are equally effective in the vibration control of the composite beam and that lms-based approach is slightly better than the derivative-based approach.
Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades the...
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Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades their performance. In this paper, a new method based on adaptive filters (AF) is proposed in order to eliminate delay and increase the response of the TCR compensator. The algorithm designed for the adaptive filters is performed based on the least mean square (lms) algorithm. In this design, instead of fixed capacitors, band-pass LC filters are used. To evaluate the filter, a TCR/FC compensator was used for nonlinear and time varying loads of electric arc furnaces (EAFs). These loads caused occurrence of power quality phenomena in the supplying system, such as voltage fluctuation and flicker, odd and even harmonics and unbalancing in voltage and current. The above design was implemented in a realistic system model of a steel complex. The simulation results show that applying the proposed control in the TCR/FC compensator efficiently eliminated delay in the response and improved the performance of the compensator in the power system. Crown Copyright (C) 2010 Published by Elsevier Ltd on behalf of ISA. All rights reserved.
Adaptive systems are employed in the cancelation of noises and estimation of periodic and quasiperiodic signals. Amongst these signals are the electrocardiogram (ECG), impedance cardiography (ZCG), brain evoked potent...
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Adaptive systems are employed in the cancelation of noises and estimation of periodic and quasiperiodic signals. Amongst these signals are the electrocardiogram (ECG), impedance cardiography (ZCG), brain evoked potentials and modulated signals in telecommunication applications. In this paper we study the behavior of the weights of the lms algorithm when used to estimate the coefficients of the discrete Fourier transform (DFT) of a signal under influence of low frequencies. We show theoretically that low frequency noise affects the estimation of the weights at higher frequencies. The simulation results obtained are in agreement with theoretical results. Moreover, we exemplify the problem with impedance cardiography (ZCG) signals. (c) 2008 Elsevier B.V. All rights reserved.
In this paper, a novel bilinear algorithm is proposed formultiple-input-single-output (MISO) system identification, which is based on a modified L-p-norm cost function with fractional lower order statistics. To model ...
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In this paper, a novel bilinear algorithm is proposed formultiple-input-single-output (MISO) system identification, which is based on a modified L-p-norm cost function with fractional lower order statistics. To model the MISO system, we employ the bilinear form (BF) which is defined with respect to the impulse responses of a spatiotemporal model. Considering the non-Gaussian behavior in practical MISO system with BF, alpha-stable distribution, whose density function decays in the tails less rapidly than the Gaussian density function, is used to model the interference noise. As an added contribution, we extend the least mean pth power (LMP) and normalized LMP (NLMP) algorithms to BF, resulting in the LMP-BF and NLMP-BF algorithms. Simulation results demonstrate the effectiveness of the proposed algorithm.
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