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Stochastic analysis of the lms algorithm for cyclostationary colored Gaussian and non-Gaussian inputs

DIGITAL SIGNAL PROCESSING 2019年 88卷 149-159页

作者： Bershad, Neil J. Eweda, Eweda Bermudez, Jose C. M. Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92660 USA C4 Adv Solut Abu Dhabi U Arab Emirates Univ Fed Santa Catarina Dept Elect Engn BR-88040900 Florianopolis SC Brazil

This paper studies the stochastic behavior of the lms algorithm in a system identification framework for a cyclostationary colored input without assuming a Gaussian distribution for the input. The input cyclostationary signal is modeled by a colored random process with periodically time-varying power. The generation of the colored non-Gaussian random process is parametrized in novel manner by passing a Gaussian random process through a coloring filter followed by a zero memory nonlinearity. The unknown system parameters are fixed in most of the cases studied here. Mathematical models are derived for the behavior of the mean and mean-square-deviation (MSD) and the excess mean-square error (EMSE) of the adaptive weights as a function of the input cyclostationarity. The models display the dependence of the algorithm upon the input nonlinearity and coloration. Three nonlinearities that are studied in detail with Monte Carlo simulations provide strong support for the theory. (C) 2019 Published by Elsevier Inc.

关键词： Adaptive filters Analysis lms algorithm Stochastic algorithms Non-Gaussian processes

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An Adaptive Echo Cancellation Module for the Same Frequency Repeater Based on lms algorithm and FPGA 13

An Adaptive Echo Cancellation Module for the Same Frequency ...

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13th IEEE International Conference on Anti-Counterfeiting, Security, and Identification (ASID)

作者： Ling, Chaodong Duan, Huipeng Lin, Wencai Huang, Ruimin Qin, Hongkai Tao, Qing Huaqiao Univ Dept Elect Engn Xiamen Peoples R China

ISBN: (纸本)9781728124582

To extend the coverage of base stations, the same frequency repeater is widely used in modern communication network However, there exists coupling echo interference between transmitting antenna and receiving antenna of the repeater station, which affects the system stability and the signal quality. The echo interference is in the same frequency with the useful signals of base stations, which cannot be eliminated by traditional frequency-domain filtering. To address this problem, this paper proposes an adaptive echo cancellation algorithm by inducing an additional reference sequences, which is targeted to apply in the hardware platform of Fujian Jingao FDD-TLE same frequency repeater. In this paper, the working principle of the algorithm is described firstly;then the algorithm is analyzed by MATLAB simulation, and finally verified in FPGA. The comparisons between before and after echo cancellation using the proposed algorithm in time domain and frequency domain shows that this algorithm can effectively suppress echo interference, and the output signal spectrum is significantly improved. Compared with the adaptive filtering algorithm based on the transform domain, this algorithm does not need Fourier transform, which has lower computational complexity and takes less resource. Moreover, this algorithm has a wide application scope and does not depend on the specific modulation scheme of the relaying signal.

关键词： echo cancellation same frequency repeater lms algorithm FPGA

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Flexible Adaptive FIR Filter Designs Using lms algorithm 23rd

Flexible Adaptive FIR Filter Designs Using LMS Algorithm

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23rd International Symposium on VLSI Design and Test

作者： Basiri, M. Mohamed Asan IIITDM Dept Elect & Commun Engn Kurnool 518007 India

ISBN: (纸本)9789813297661;9789813297678

This paper proposes the least mean square (lms) algorithm based versatile, vector, and fault tolerant adaptive finite impulse response (FIR) filter designs. Here, the M-taps versatile design is to perform the filter operation with the number of filter co-efficients varied from 2 to M. The M-taps vector design is to perform left perpendicular left perpendicular M/L right perpendicular numbers of L-taps filter operations in parallel, where M >= L. The fault tolerantM-taps filter is to perform the (M - N)-taps fault free filter operation under the N numbers of faulty filter kernels, where (M - N) >= 2. All the existing and proposed designs are implemented with 45 nm CMOS technology. The proposed 16-taps vector adaptive filter design achieves 93% of improvement in throughput as compared with the distributed arithmetic based design.

关键词： Adaptive filter FIR filter lms algorithm

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Trend Removal of ECG Signal with lms algorithm

Trend Removal of ECG Signal with LMS Algorithm

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Medical Technologies Congress (TIPTEKNO)

作者： Bozok, Buse Arica, Sami Cukurova Univ Elect & Elect Engn Dept Adana Turkey

ISBN: (纸本)9781728124209

In this study, the lms algorithm was employed to detect and track baseline wanders introduced during the acquisition of electrocardiogram signals. The baseline wander was removed from the signal and ECG is corrected. For this purpose, the baseline signal was modeled as a constant and a line in the lms algorithm. The two approaches were applied to the signals received from MIH-BIH database records and the results were reported and compared. When the experimental results are investigated it is observed that the line model adapts faster and tracks baseline wander.

关键词： lms algorithm ECG baseline signal suppression adaptive filter

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A Simple Sparsity-aware Feature lms algorithm 27

A Simple Sparsity-aware Feature LMS Algorithm

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27th European Signal Processing Conference (EUSIPCO)

作者： Chaves, Gabriel S. Lima, Markus V. S. Yazdanpanah, Hamed Diniz, Paulo S. R. Ferreira, Tadeu N. Fed Univ Rio de Janeiro UFRJ Poli POB 68504 BR-21941972 Rio De Janeiro RJ Brazil Fed Univ Rio de Janeiro UFRJ COPPE POB 68504 BR-21941972 Rio De Janeiro RJ Brazil Univ Sao Paulo Dept Comp Sci Inst Math & Stat Rua Matao 1010 BR-05508090 Sao Paulo Brazil Fluminense Fed Univ UFF Engn Sch Rua Passo Patria 56 Block E Room 406 BR-24210240 Niteroi RJ Brazil

ISBN: (纸本)9789082797039

Many real systems have inherently some type of sparsity. Recently, the feature least-mean square (F-lms) has been proposed to exploit hidden sparsity. Unlike the existing algorithms, the F-lms algorithm performs a linear combination of the adaptive coefficients to reveal and then exploit the hidden sparsity. However, many systems have also plain besides hidden sparsity, and the F-lms algorithm is not able to exploit the former. In this paper, we propose a new algorithm, named simple sparsity-aware F-lms (SSF-lms) algorithm, that is capable of exploiting both kinds of sparsity simultaneously. The hidden sparsity is exploited just like in the F-lms algorithm, whereas the plain sparsity is exploited by means of the discard function applied to the filter coefficients. By doing so, the proposed SSF-lms algorithm not only outperforms the F-lms algorithm when plain sparsity is also observed, but also requires fewer arithmetic operations. Numerical results show that the proposed algorithm has faster speed of convergence and reaches lower steady-state mean-squared error (MSE) than the F-lms and classical algorithms, when the system has plain and hidden sparsity.

关键词： adaptive filtering lms algorithm feature matrix discard function sparsity

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Implementation of lms algorithm for image noise cancellation 5

Implementation of LMS algorithm for image noise cancellation

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5th International Conference on Computing, Communication Control and Automation (ICCUBEA)

作者： Bansal, Shruti S. Bhandari, Sheetal U. Thorbole, Pradip S. PCCOE Dept Elect & Telecommun Engn Pune Maharashtra India CoreEL Technol Dept Elect & Telecommun Engn Pune Maharashtra India

ISBN: (纸本)9781728140421

Noise is the unwanted signal that is added at the time of transmission of signals(data, audio, images or video). These unwanted noisy signals degrades the quality of original information signal. Since these noise parameters are not known in advance, these can be cancelled out effectively by using adaptive filters. Least mean squares (lms) algorithm is one of the algorithms in adaptive filters used to find the filter coefficients used to reduce the noise signal. Focus of this paper will be to develop a simulink model to attenuate noise and recover the original image signal.

关键词： Adaptive filter lms algorithm Image Noise Cancellation

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Feature lms algorithm for Bandpass System Models 27

Feature LMS Algorithm for Bandpass System Models

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27th European Signal Processing Conference (EUSIPCO)

作者： Diniz, Paulo S. R. Yazdanpanah, Named Lima, Markus V. S. Univ Fed Rio de Janeiro Dept Elect & Elect Engn Rio De Janeiro Brazil Univ Sao Paulo Dept Comp Sci Inst Math & Stat Sao Paulo Brazil

ISBN: (纸本)9789082797039

Sparse representations of model parameters have been widely studied. In the adaptive filtering literature, most studies address the cases where the sparsity is directly observed, therefore, there is a growing interest in developing strategies to exploit hidden sparsity. Recently, the feature lms (F-lms) algorithm was proposed to expose the sparsity of models with low- and high-frequency contents. In this paper, the F-lms algorithm is extended to expose hidden sparsity related to models with bandpass spectrum, including the cases of narrowband and broader passband sources. Some simulation results show that the proposed approaches lead to F-lms algorithms with fast convergence, low misadjustment after convergence, and low computational cost.

关键词： adaptive filtering lms algorithm feature matrix bandpass system narrowband system

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A sparse variable step-size lms algorithm for impulsive noise 3

A sparse variable step-size LMS algorithm for impulsive nois...

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3rd International Conference on Bio-engineering for Smart Technologies (BioSMART)

作者： Salman, Mohammad Shukri El-Sayed, Fahmi Youssef, Ahmed Amer Univ Middle East Coll Engn & Technol Egaila Kuwait

ISBN: (纸本)9781728135786

In sparse system identification, exploiting the sparsity property improves the performance of the least mean square (lms) algorithm. The improvement is achieved by adding an l(0) or l(1)-norm penalty term to the cost function of the conventional lms algorithm. However, when the eignenvalue spread of the autocorrelation of the input is relatively large, the performance of the lms algorithm is poor. For instance, the lms algorithm cannot perform accurate system identification under the impulsive noise environment because its cost function is not well defined for such scenarios. In this paper, we propose a sparse variable step-size lms algorithm that employs arctan constraint in the cost function of the algorithm. This constraint imposes a zero attraction of the filter coefficients according to the relative value of each filter coefficient among all the entries. This, in turn, leads to an improved performance when the system is sparse. Different experiments have been conducted to investigate the performance of the proposed algorithm. Simulation results show that the proposed algorithm outperforms the zero attracting lms (ZA-lms) and the reweighted ZA-lms (RZA-lms) algorithms in a system identification setting under impulsive noise environment.

关键词： lms algorithm Sparse lms algorithm VSSlms algorithm Sparse system

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An improved lms algorithm for active sound-quality control of vehicle interior noise based on auditory masking effect

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2018年 108卷 292-303页

作者： Wang, Y. S. Feng, T. P. Wang, X. L. Guo, H. Qi, H. Z. Shanghai Univ Engn Sci Sch Automot Engn 333 Longteng Rd Shanghai 201620 Peoples R China Univ Shanghai Sci & Technol Sch Mech Engn Shanghai 200093 Peoples R China

Based on the adaptive least mean square (lms) algorithm commonly used in active noise control (ANC), an improved active sound-quality control (ASQC) method for vehicle interior noise, so-called post-masking lms (Pmlms) algorithm, is presented in this paper. Aiming at sound loudness index of measured vehicle interior noises, the Pmlms is derived by considering the post-masking effect of human auditory system. Through adjusting the sizes of iteration step in simulations, it is proven that the newly proposed Pmlms has similar properties as those of the lms. Comparisons of simulation experiment show that, under the same conditions of appropriate iteration step, filter order and target noise signal, the ASQC results from the Pmlms are better than those from the lms algorithm, which suggests an effective control of vehicle interior noise. In applications, if one may reasonably match the size of iteration step and vehicle running speed, the Pmlms algorithm can be directly used in ASQC system of a vehicle for improving the ride comfort of passengers. The proposed Pmlms algorithm as a promising method may be further extended to the filtered-x lms (Fxlms) and applied in other ANC fields for sound quality control in engineering. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Active sound-quality control Vehicle interior noise lms algorithm Post-masking effect

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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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