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Analysis of a Diffusion lms algorithm with Probing Delays for Cyclostationary White Gaussian and Non-Gaussian Inputs

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SIGNAL PROCESSING 2024年 219卷

作者： Eweda, Eweda Bermudez, Jose C. M. Bershad, Neil J. Future Univ Dept Elect Engn Cairo Egypt Univ Fed Santa Catarina Dept Elect Engn Florianopolis SC Brazil Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92660 USA

The paper studies the behavior of the diffusion least mean square (Dlms) algorithm in the presence of delays in probing the unknown system by the nodes. The types of input distribution and the probing delays can be different for different nodes. The analysis is done for a network having a central combiner. This structure reduces the dimensionality of the resulting stochastic models while preserving important diffusion properties. Communication delays between the nodes and the central combiner are also considered in the analysis. The analysis is done for system identification for cyclostationary white nodal inputs. Mean and mean -square behaviors of the algorithm are analyzed. The derived models consist of simple scalar recursions. These recursions facilitate the understanding of the algorithm mean and mean -square dependence upon the 1) nodal input kurtosis, 2) nodal probing delays, 3) communication delays between the nodes and the central combiner, 4) nodal noise powers, and 5) nodal weighting coefficients. Significant differences are found between the algorithm behavior for equal probing delays and that for unequal probing delays. Results for unequal probing delays are surprising. Simulations are in excellent agreement with the theory.

关键词： Adaptive filters Analysis lms algorithm Stochastic diffusion algorithms

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Stochastic analysis of the diffusion lms algorithm for cyclostationary white Gaussian inputs

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SIGNAL PROCESSING 2021年 185卷 108081-108081页

作者： Bershad, Neil J. Eweda, Eweda Bermudez, Jose C. M. Univ Calif Irvine Dept Elect Engn & Comp Sci 1621 Santiago Dr Newport Beach CA 92660 USA Future Univ Dept Elect Engn New Cairo Egypt Univ Fed Santa Catarina Dept Elect Engn BR-88040900 Florianopolis SC Brazil

This paper studies the stochastic behavior of a specific version of the Diffusion Least-Mean Square (Dlms) algorithm in a system identification framework for a cyclostationary white Gaussian input. The considered Dlms version has a fusion center. The input cyclostationary signal is modeled by a white random process with periodically time-varying power. The system parameters vary according to a random walk model. The paper focusses on the behavior of the fusion center for Dlms for the special case when the nodes communicate only with the fusion center and vice versa. Mathematical models are derived for the mean and mean-square-deviation (MSD) behavior of the fusion center adaptive weights as a function of the input cyclostationarity. It is shown that the behavior of the fusion center is the same for both Combine-Then-Adapt (CTA) and Adapt-Then-Combine (ATC) diffusion strategies. Monte Carlo simulations are shown in excellent agreement with the theory. Finally the model is used to study the design of the Dlms algorithm for different nodal step-sizes, cyclostationarities, noise powers and weighting co-efficients. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Adaptive filters Analysis lms algorithm Stochastic diffusion algorithms

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Performance analysis of a Fourier coefficient estimation method using IIR-BPFs and an lms algorithm and improvement of its performance

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ELECTRONICS AND COMMUNICATIONS IN JAPAN PART III-FUNDAMENTAL ELECTRONIC SCIENCE 2002年第12期85卷 19-28页

作者： Kudoh, N Tadokoro, Y Hachinohe Inst Technol Hachinohe 0391192 Japan Toyohashi Univ Technol Fac Engn Toyohashi Aichi 4418580 Japan

In many areas, it is extremely important to accurately estimate the amplitude and phase of a signal even if the frequency contained in the signal to be analyzed is known. For cases in which the signal frequencies to be analyzed are in a nonharmonic relation and white noise and interference are superposed on the signal, a method (BPlms method) combining the IIR type BPF and the lms algorithm has been proposed to derive the Fourier coefficients of the signal components accurately. In the present paper, in order to investigate a method of improving the BPlms method, an approximate equation for the estimated accuracy is derived. Also, the validity of the approximate equation is confirmed by computer simulations under various conditions. As a result of the approximate analysis, it is shown that the normalized frequency difference between the signal and the interference can be increased by combining a down-sampling process so that the estimation accuracy can be improved. Finally, by simulation, the proposed method and the BPlms method are compared in terms of estimation accuracy. An example of application to the pitch estimation of musical sounds is given. (C) 2002 Wiley Periodicals, Inc.

关键词： HR notch filter lms algorithm NFT nonharmonic signal downsampling process

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Design and experimental evaluation of feedforward controller integrating filtered-x lms algorithm with applications to electro-hydraulic force control systems

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Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 2015年第12期230卷 1951 - 1967页

作者： Yu Tang Zhencai Zhu Gang Shen School of Mechanical and Electrical Engineering China University of Mining and Technology Xuzhou ChinaJiangsu Key Laboratory of Mine Mechanical and Electrical Equipment China University of Mining and Technology Xuzhou China

The control purpose of an electro-hydraulic force control (EHFC) system is to real time replicate the force exerted on a structure in laboratory so as to simulate loads that cannot otherwise be generated naturally. In contrast to electro-hydraulic position control system, the tracking performance of EHFC system is always limited. To enhance the force replication accuracy of EHFC systems, a feedforward inverse controller integrating filtered-x lms adaptive algorithm is presented in this paper. The proposed controller comprises a feedforward inverse controller and an adaptive controller. The feedforward inverse controller working as an inner loop is firstly established by directly cascading the designed parametric inverse transfer function to the EHFC system with proportional integral controller and the inverse transfer function is obtained with the implementation of system identification and zero magnitude error tracking technology. Then, the adaptive controller employing the filtered-x lms algorithm acting as an outer loop is further combined with the feedforward controller to deal with the error occurred in the inverse model design procedure. Therefore, the proposed controller is an easy-to-implement strategy and can effectively enhance the force replication performance for both phase delay errors and amplitude mismatch errors. Finally, a series of experiments are carried out on a real EHFC test rig by means of xPC target technology, and the experimental results indicate that the proposed controller has a relatively better tracking accuracy compared with the proportional integral controller and the feedforward controller. It is also worth noting that the proposed controller can also be extended to other servo control systems where high accuracy tracking performance is required.

关键词： Electro-hydraulic system force control feedforward control adaptive control lms algorithm

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Identification for Hammerstein nonlinear systems based on universal spline fractional order lms algorithm

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2019年 79卷 104901-000页

作者： Cheng, Songsong Wei, Yiheng Sheng, Dian Wang, Yong Univ Sci & Technol China Dept Automat Hefei 230027 Anhui Peoples R China

In this paper, we investigate the identification problem of the Hammerstein nonlinear systems. In order to approximate the nonlinear block and for the convenience of analyzing the convergence of the proposed algorithm, we modify the conventional spline interpolation such that the nonlinear output signal can be expressed in a universal form. Besides, we develop a fractional order lms (Least-Mean-Square) algorithm to identify the linear block and control points of the nonlinear block and establish the convergence properties of the algorithm by employing the stability theory of fractional order difference systems. Finally, we also provide two numerical examples to illustrate the effectiveness of the proposed algorithm. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Fractional order difference lms algorithm Stability Spline interpolation Nonlinear system identification

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Denoising low SNR percussion acoustic signal in the marine environment based on the lms algorithm

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MEASUREMENT 2022年 202卷

作者： Yang, Zhuodong Huo, Linsheng Wang, Jingkai Zhou, Jing Dalian Univ Technol State Key Lab Coastal & Offshore Engn Dalian Peoples R China

Percussion-based inspection of structures has attracted widespread attention in recent years. However, the percussion acoustic signals collected in the marine environment usually have a low signal-to-noise ratio (SNR) and are difficult to use directly due to the interference by a multitude of marine noises. The frequency contents of the ambient noises usually overlap with those of the percussion acoustic signals, thus limiting the denoising using traditional methods. This paper proposes a denoising method using the least mean square (lms) algorithm to obtain the approximate percussion signal. The noisy percussion signals and marine noise are recorded syn-chronously by two hydrophones. Then the lms algorithm processes the collected signals and provides the fre-quency peaks that cannot be extracted with conventional methods. The proposed method is validated by experiments conducted in a noiseless laboratory environment and a noisy, naturally occurring marine envi-ronment. The results reveal that the proposed method is excellent in denoising the raw signal, and the error is about 3% in terms of differences in the estimated value of the primary peak frequency. This study demonstrates the broad potential for the method to be applied toward damage detection for underwater structures.

关键词： lms algorithm Marine noise Percussion acoustic signal Signal denoising

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Harmonic Fractional Detection Based on The lms algorithm

World Scientific Research Journal

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World Scientific Research Journal 2023年第4期9卷 156-164页

作者： Jianjun Sun

In the power system, there are many power electronic equipment in use. There are a lot of harmonics in the power system because of their nonlinear properties. These harmonics have a huge impact on the power grid. To filter out these harmonics, some harmonic detection methods are needed. This work suggests using the lms algorithm to detect each harmonic in order due to the complexity of all current harmonic detection algorithms or the fact that only the total harmonic components other than the fundamental wave may be discovered. This technique can quickly determine the amplitude and phase size of each harmonic component in addition to having a straightforward procedure. By creating a Matlab Simulink simulation model, the efficacy of this approach is confirmed.

关键词： Harmonic fractional detection lms algorithm Matlab Simulink simulation

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On the Robustness of lms algorithm

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IFAC Proceedings Volumes 1996年第1期29卷 4622-4627页

作者： Vladislav Tadić Automatic Control Laboratory Mihailo Pupin Institute Volgina 15 11000 Belgrade Yugoslavia - Serbia

Robustness of the Least Mean Square algorithm (lms) with respect to non-additive noise is considered in this paper. Under very general assumptions, an almost sure upper bound for the asymptotic deviation of algorithm ... 详细信息

关键词： Robustness lms algorithm signal processing

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MC-CDMA System Identification and Equalization Using the lms algorithm and Takagi-Sugeno Fuzzy System

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IFAC Proceedings Volumes 2013年第11期46卷 599-604页

作者： S. Safi M. Frikel M. Pouliquen I. Badi Y. Khmou M. Boutalline Department of Mathematics and Informatics Sultan Moulay Slimane University Po. Box: 592 Beni Mellal Morocco ENSICAEN School GREYC Laboratory6 B. Marchal Juin 14050 Caen France Polydisciplinary Faculty Sultan Moulay Slimane University Beni Mellal Morocco

In this paper we are focused on the Multi-Carrier Code Division Multiple Access (MC-CDMA) equalization problem. The equalization is performed using the Minimum Mean Square Error (MMSE) and Zero Forcing (ZF) equalizer based on the identified parameters representing the indoor scenario (European Telecommunications Standards Institute Broadband Radio Access Networks (ETSI BRAN A) channel model), and outdoor scenario (ETSI BRAN E channel model). These channels are normalized for fourth-generation mobile communication systems. However, for such high-speed data transmissions, the channel is severely frequency-selective due to the presence of many interfering paths with different time delays. The identification problem is performed using the Least Mean Squares (lms) algorithm and the Takagi-Sugueno (TS) fuzzy system. The comparison between these techniques, for the channel identification, will be made for different Signal to Noise Ratios (SNR).

关键词： lms algorithm Takagi-Sugeno fuzzy system MC-CDMA system Identification and Equalization

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Variable Step Size lms algorithm using Squared Error and Autocorrelation of Error

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Procedia Engineering 2012年 41卷 47-52页

作者： Hong Chae Woo Daegu University Jinryang Gyungsan Gyungbuk 712-714 Rep. of Korea

A variety of different approaches in the variable step adjustment algorithm of the lms were researched to achieve fast convergence and robustness, but the complexity of the variable step algorithm was also become higher. A variable step size lms algorithm using squared error and autocorrelation of error is proposed to achieve fast convergence and robustness under reasonable complexity. The performance of the proposed lms algorithm is analyzed in a stationary environment. The proposed algorithm is tested under an adaptive equalizer system and showed good convergence rate and robustness to disturbance.

关键词： Adaptive filter lms algorithm adaptive equaltizer

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