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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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Analysis on the adaptive filter based on lms algorithm

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OPTIK 2016年第11期127卷 4698-4704页

作者： Zhu, Zhen Gao, Xiang Cao, Leilei Pan, Daoyuan Cai, Yumeng Zhu, Yu Jiangsu Univ Sch Automot & Traff Engn Zhenjiang 212013 Peoples R China Anhui Polytech Univ Sch Mech & Automot Engn Wuhu 241000 Peoples R China IVECO Co Ltd Axle Branch Co Nanjing 212028 Jiangsu Peoples R China

This article focuses on the application of adaptive filter based on the lms algorithm. An adaptive filter of the closed-loop system is introduced, including the elimination of interference signal, the prediction of useful signal, and the approximation of expected signal. lms (Least Mean Square) algorithm is used to meet the optimum norm of error between estimated signal and expected signal. The structure of lms algorithm is presented and the simulation of lms algorithm is carried out. The results indicate that the convergence performances of lms algorithm are prefect, and the input signal can converge to the expected signal. The application of adaptive filtering technology in this article includes the correction of channel mismatch by an adaptive linear filter, the improvement of system performance by an adaptive equalizer, and the filter of frequency signal by an adaptive notch filter. The analysis on adaptive linear filter shows that the constant channel mismatch can be corrected quite well by the correction algorithm. The analysis on adaptive equalizer shows that the error rate of system with an adaptive equalizer has significant improvement gains over that of system without an adaptive equalizer. The smaller the error rate, the larger the SNR. The relationship between error rate and multi-path loss show that the error rate is largest when the loss factor is 0.5. The analysis on adaptive notch filter shows that the interference signal with two different known frequencies can be eliminated effectively by the adaptive notch filter. The filtered signals accord with the corresponding useful signals very well. (C) 2016 Published by Elsevier GmbH.

关键词： Adaptive filter lms algorithm Adaptive linear filter Adaptive equalizer Adaptive notch filter

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Design and performance analysis of lms algorithm based adaptive filter embedded with CFAR detector under non-homogeneous clutter scenarios

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2016年第7期30卷 941-956页

作者： Mandal, Amritakar Mishra, Rajesh Gautam Buddha Univ Sch Informat & Commun Technol Greater Noida 201308 India

The paper presents performance analysis of least-mean-square algorithm based adaptive filter embedded with constant false alarm rate (CFAR) detector for the purpose of better detection of target under non-homogeneous clutter environment in radar application. The objective of this paper is to develop a method by redesigning the radar detector in such a way to emphasize the target response and de-emphasize the clutter response. The hardware implementation using pipeline technique for the adaptive filter reveals its capability to support high sampling frequency, which is an ardent necessity for high performance radar. The moderate area-delay-product and low power consumption have made it suitable for hardware realization for such application. The extensive MATLAB simulation of proposed design shows remarkable improvement of detection performance in terms of signal-to-noise ratio of 17dB considering probability of detection at 0.8 over the generic cell averaging CFAR (CA-CFAR). Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： digital filters pipeline design CFAR clutter signal-to-noise ratio (SNR) adaptive filter lms algorithm

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Lp-norm of the lms algorithm for bilinear forms with α-stable processes

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MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING 2020年第1期31卷 191-203页

作者： Lu, Lu Yu, Yi Sichuan Univ Sch Elect & Informat Engn Chengdu 610065 Peoples R China Southwest Univ Sci & Technol Sch Informat Engn Mianyang 621010 Sichuan Peoples R China

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.

关键词： lms algorithm Bilinear form alpha-stable noise Convergence analysis Multiple-input-single-output (MISO) model

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Statistical-Mechanical Analysis of Adaptive Volterra Filter with the lms algorithm

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2021年第12期E104A卷 1665-1674页

作者： Motonaka, Kimiko Koseki, Tomoya Kajikawa, Yoshinobu Miyoshi, Seiji Kansai Univ Fac Engn Sci Dept Elect Elect & Informat Engn Suita Osaka 5648680 Japan JB Toll Syst Co Ltd Kobe Hyogo 6510084 Japan

The Volterra filter is one of the digital filters that can describe nonlinearity. In this paper, we analyze the dynamic behaviors of an adaptive signal-processing system including the Volterra filter by a statistical-mechanical method. On the basis of the self-averaging property that holds when the tapped delay line is assumed to be infinitely long, we derive simultaneous differential equations in a deterministic and closed form, which describe the behaviors of macroscopic variables. We obtain the exact solution by solving the equations analytically. In addition, the validity of the theory derived is confirmed by comparison with numerical simulations.

关键词： Volterra filter adaptive filter statistical-mechanical informatics lms algorithm

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PROPERTIES OF THE MOMENTUM lms algorithm

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SIGNAL PROCESSING 1989年第2期18卷 117-127页

作者： TUGAY, MA TANIK, Y Department of Electrical and Electronics Engineering Middle East Technical University Ankara Turkey

One of the most recent modifications on Widrow and Hoff's lms algorithm has been the inclusion of a momentum term into the weight update equation. The resulting algorithm is referred to as “The Momentum lms (Mlms) algorithm”. This paper revises the basic properties of the Mlms algorithm for stationary inputs. As a result, new bounds, on the parameters of the algorithm, for convergence are found, and it is shown that, under slow convergence conditions, this new algorithm is equivalent to the usual lms algorithm, but it outperforms the lms algorithm for fast convergence cases and for inputs containing inpulsive noise components. Zusammenfassung Eine der neuesten Modifikationen des “Kleinste-Quadrate-(lms) algorithmus” nach Widrow und Hoff war die Einführung eines Momenten-Terms in die Beziehung, mit der die Gewichte aktualisiert werden. Der so entstandene algorithmus wird “Momenten-lms-(Mlms) algorithmus” gennant. Im folgenden Beitrag werden die Grundeigenschaften des Mlms-Verfahrens für stationäre Signale neu dargestellt. Das führt zu neuen Konvergenz-Grenzwerten für die Parameter des algorithmus'. Es wird gezeigt, daβ das Verfahren unter den Bedingungen langsamer Konvergenz der gewöhnlichen lms-Methode gleichwertig ist, im Falle schneller Konvergenz sowie bei Signalen mit Impulsstörungen jedoch besser arbeitet.

关键词： lms algorithm Mlms algorithm Back Propagation Training algorithm misadjustment adaptive predictor

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lms algorithm Derivatives used in Real-Time Filtering of ECG Signals: A Study Case on Performance Evaluation

LMS Algorithm Derivatives used in Real-Time Filtering of ECG...

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International Conference and Exposition on Electrical and Power Engineering (EPE)

作者： Tudosa, Ioan Adochiei, Narcis Gheorghe Asachi Tech Univ Iasi Fac Elect Engn Iasi Romania

ISBN: (纸本)9781467311724;9781467311731

The paper presents two derivatives of the Least Mean Square (lms) algorithm, which can be utilized in real-time processing of the electrocardiographic (ECG) signals: (i) the Normalized lms (Nlms), and (ii) Sign based lms (S-lms) algorithms. The algorithms are suitable for implementation on Digital Signal Processors (DSPs) or on Field Programmable Gates Arrays (FPGAs), and the practical implementations of their equations are presented. The implementation of the iterative steps can be done in an easy manner with low computational complexity with good effect on the filtering process, for both types of perturbations, electronic noises and power line interference signals, which can occur on ECG signals.

关键词： adaptive filter ECG signal processing real-time signal processing lms algorithm

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Analysis of a Diffusion lms algorithm With Communication Delays for Cyclostationary White Gaussian Inputs

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2022年 8卷 960-972页

作者： Eweda, Eweda Bermudez, Jose C. M. Bershad, Neil J. Future Univ Dept Elect Engn Cairo 11835 Egypt Univ Fed Santa Catarina Dept Elect Engn BR-88040900 Florianopolis SC Brazil Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA 92660 USA

Available analyses of the diffusion lms (Dlms) algorithm assume that the nodes probe the unknown system with zero delay. This assumption is unrealistic, since the unknown system is usually distant from the nodes. The present paper studies the behavior of the algorithm without this assumption. 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 Gaussian nodal inputs. Mean and mean-square behaviors of the algorithm are analyzed. It is found that delays in probing the unknown system yield a bias in the algorithm without increasing its convergence time. The communication delays between the nodes and the central combiner increase the convergence time without affecting the steady-state behavior. The stability of the algorithm is not affected by either type of delay. The analysis exactly matches the simulations.

关键词： Adaptive filters analysis diffusion algorithms distributed adaptation over networks EDICS ADEL-DAN (Distributed adaptation over networks) lms algorithm

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A Novel lms algorithm with Double Fractional Order

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第2期42卷 1236-1260页

作者： Zhang, Haozhe Mo, Lipo Beijing Technol & Business Univ Sch Math & Stat Beijing 100048 Peoples R China Beijing Technol & Business Univ Res Ctr Consumpt Big Data & Intelligent Decis Mak Beijing 100048 Peoples R China

This paper presents a double fractional order lms algorithm (DFOlms) based on fractional order difference and fractional order gradient, in which a variable initial value strategy is introduced to ensure the convergence accuracy of the algorithm. Through a model approximation, the DFOlms is transformed into two fractional order difference models to analyze its convergence and steady-state properties indirectly. It is shown that the DFOlms has different convergence characteristics in different difference intervals;meanwhile, a larger difference order a and gradient order beta would lead to a faster convergence speed but a larger steady-state noise. Finally, the effectiveness and superiority of the proposed DFOlms are demonstrated by simulation examples.

关键词： lms algorithm Fractional order difference Fractional order gradient Convergence speed Steady-state noise

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Modified clipped lms algorithm

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EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING 2005年第8期2005卷 1229-1234页

作者： Lotfizad, M Yazdi, HS Tarbiat Modarres Univ Dept Elect Engn Tehran Iran

A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped lms, and uses a three-level quantization (+1, 0, -1) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped lms (MClms) algorithm has better tracking than the lms algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MClms algorithm compared to the lms algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.

关键词： adaptive filter lms algorithm clipped lms algorithm modified dipped lms algorithm

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