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Robust variable step size Widely Linear Complex-Valued Least Mean M-estimate Adaptive Algorithm: Derivation and Performance Analysis

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2024年第6期43卷 3888-3908页

作者： Lv, Shaohui Zhao, Haiquan Xu, Wenjing Southwest Jiaotong Univ Key Lab Magnet Suspens Technol & Maglev Vehicle Minist Educ Chengdu 610031 Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu 610031 Peoples R China

In the past decade, the augmented complex-valued least mean square adaptive filtering algorithm based on the minimum mean square error criterion and widely-linear model has attracted much attentions due to its simplicity and applicability to non-circular signals. However, the system noise with impulse characteristics will dramatically affect the convergence of the augmented complex-valued least mean square algorithm. Recently, a robust widely-linear complex-valued least mean M-estimate algorithm has been proposed, which significantly improves the robustness of the augmented complex-valued least mean square algorithm to impulsive noise. But it should be noted that the widely-linear complex-valued least mean M-estimate algorithm with fixed step size faces the trade-off between convergence speed and steady-state accuracy. To overcome this drawback, a variable step size widely-linear complex-valued least mean M-estimate algorithm is presented in this paper, in which the optimal step size at each iteration is obtained by maximizing the difference between the mean square deviations of the WL-CLMM algorithm at adjacent moments. In order to reveal the statistical convergence behavior of the proposed variable-step-size widely-linear complex-valued least mean M-estimate algorithm to better guide the parameter selection in practical applications. Theoretical transient and steady-state mean-square deviation convergence behaviors of the variable-step-size widely-linear complex-valued least mean M-estimate algorithm are analyzed and the corresponding mean-square deviation expressions are also derived. Computer simulations on system identification and stereophonic acoustic echo cancellation in impulsive noise environments confirm the validity of the analysis results and the performance improvement from the variable step size strategy.

关键词： Complex-valued adaptive filter Impulsive noise Performance analysis M-estimate variable-step-size Stereophonic acoustic echo cancellation

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Parameter estimation and tracking of sinusoid using variable-step-size LMS algorithms

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OPTIK 2016年第22期127卷 10953-10960页

作者： Garg, Rohit Kohli, Amit Kumar Thapar Univ Dept Elect & Commun Engn Patiala 147004 Punjab India

In this paper, we present the performance evaluation of different variable-step-size (VSS) least-mean-square (LMS) algorithms, which are used for parameter estimation of sinusoidal signals in sensor networks. The VSS in LMS algorithm is not only varied based on the error and input signal correlations, but also it can be varied by using sigmoid function as an alternative approach. The performance of VSS-LMS algorithm is appraised on the basis of convergence and tracking characteristics, in terms of mean-squared-error (MSE), when delay as well as amplitude need to be estimated. Simulation results are presented to illustrate efficiency and efficacy of both types of VSS criteria in combination with LMS algorithm. (C) 2016 Elsevier GmbH. All rights reserved.

关键词： Adaptation characteristics variable-step-size LMS Amplitude estimation Delay estimation

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Zero-attracting variable-step-size least mean square algorithms for adaptive sparse channel estimation

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2015年第9期29卷 1189-1206页

作者： Li, Yingsong Hamamura, Masanori Kochi Univ Technol Grad Sch Engn Kami 7828502 Japan

Recently, sparsity-aware least mean square (LMS) algorithms have been proposed to improve the performance of the standard LMS algorithm for various sparse signals, such as the well-known zero-attracting LMS (ZA-LMS) algorithm and its reweighted ZA-LMS (RZA-LMS) algorithm. To utilize the sparsity of the channels in wireless communication and one of the inherent advantages of the RZA-LMS algorithm, we propose an adaptive reweighted zero-attracting sigmoid functioned variable-step-size LMS (ARZA-SVSS-LMS) algorithm by the use of variable-step-size techniques and parameter adjustment method. As a result, the proposed ARZA-SVSS-LMS algorithm can achieve faster convergence speed and better steady-state performance, which are verified in a sparse channel and compared with those of other popular LMS algorithms. The simulation results show that the proposed ARZA-SVSS-LMS algorithm outperforms the standard LMS algorithm and the previously proposed sparsity-aware algorithms for dealing with sparse signals. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： least mean square sparse channel estimation compressed sensing zero-point attracting l(1)-penalized least mean square variable-step-size adaptive filtering

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Two-channel variable-step-size forward-and-backward adaptive algorithms for acoustic noise reduction and speech enhancement

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SIGNAL PROCESSING 2015年 108卷 226-244页

作者： Bendoumia, Redha Djendi, Mohamed Univ Blida 1 Signal Proc & Image Lab LATSI Blida 09000 Algeria

This paper addresses the problem of speech enhancement and acoustic noise reduction by adaptive filtering algorithms. Recently, forward-and-backward (FB) blind-sourceseparation (BSS) structures have been proposed to solve acoustic noise reduction and speech enhancement problems. The FB structures use the least-mean-square (LMS) algorithm in combination with two BSS structures and are implemented with fixed-step-size to control the convergence behavior of the cross-coupling adaptive filters. In this paper, we propose two new two-channel variable-step-size FB algorithms (2C-VSSF and 2C-VSSB) that improve the previous LMS-based algorithm in the transient and the steady-state phases. These two new proposed FB algorithms are based on recursive formulas, which lead to efficient estimation of the optimal step-sizes of the cross-coupling filters. These proposed algorithms show significant improvement in the steady-state and transient mean-square-error (MSE) values. We present simulation results of the proposed 2C-VSSF and 2C-VSSB algorithms that confirm the superiority and good performance in comparison with the original versions, which use fixed-step-sizes. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Speech enhancement Acoustic noise reduction variable-step-size MSE Output signal-to-noise ratio (SNR) Cepstral distortion (CD) System mismatch (SM)

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A Quaternionic Extension Algorithm of the Nonlinear Transformation for Active Impulsive Noise Control

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2025年第1期44卷 592-615页

作者： Zhang, Bingyan Chen, Xiaomei Zhong, Bo North China Elect Power Univ Dept Elect & Elect Engn Beijing 102206 Peoples R China Natl Inst Metrol Dept Mech Beijing 100029 Peoples R China Natl Inst Metrol Acoust Div Beijing 100029 Peoples R China

The classical filtered-x least-mean-square (FxLMS) algorithm, which only accepts real-valued parameter operations, is insufficient in active impulsive noise control systems. The quaternion algorithms have better geometric properties than the real-valued and complex-valued algorithms. The paper proposes a filtered-x quaternion-valued least-mean-square algorithm of the arctangent nonlinear transformation, which is defined as the FxatanQLMS algorithm. FxatanQLMS uses the quaternion-valued least mean square (QLMS) as the core filter to operate multi-dimensional signals as single quaternion entities, and it uses the arctangent function to nonlinearly transform the error signal to smoothly adjust and constrain the update of the weight coefficients. To optimize the convergence capability, a variable-step-size FxatanQLMS (SHVSS-FxatanQLMS) algorithm containing a composite relationship that combines the sigmoid (S) function and harmonic (H) mean of the error signal, is presented to compress the error signal. Simulation studies on an impulsive-noise environment with a symmetric alpha\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}-stable (S alpha\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}S) distribution validate the proposed algorithms compared to other methods in terms of the convergence rate and noise reduction performance.

关键词： Active noise control Quaternion-valued Nonlinear transformation variable-step-size Impulsive noise

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DBVSB-P-RRT*: A path planning algorithm for mobile robot with high environmental adaptability and ultra-high speed planning

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 266卷

作者： Guo, Shengjie Gong, Junjie Shen, Haotian Yuan, Lili Wei, Wei Long, Yu Guangxi Univ State Key Lab Featured Met Mat & Life cycle Safety Nanning 530004 Peoples R China Nanning Univ Sch Mech Engn Guangxi Key Lab Int Join China ASEAN Comprehens Tr Nanning 530000 Peoples R China Northwestern Polytech Univ Inst Data Sci & Intelligent Syst Xian 710072 Peoples R China

To address the limitations of the rapidly-exploring random tree star (RRT*) algorithm, such as slow convergence, high time cost, and weak environmental adaptability, which have hindered its application in the field of mobile robot path planning, this paper introduces a bi-directional P-RRT* algorithm with adaptive direction biased and variable-step-size (DBVSB-P-RRT*). In the sampling phase, anew adaptive target deviation sampling mechanism is designed to alter the sampling angle during the planning process based on the obstacle configuration between the continuously iterated new node and the target point. In the RRT* extension phase, improvements are made to the attractive potential field (APF) algorithm, and an adaptive step size is devised to enhance environmental adaptability and guidance by integrating with the RRT* algorithm. Additionally, a collision detection function has been designed to preemptively eliminate a portion of obstacles, thereby reducing the number of iterations and enhancing the efficiency of the planning process. In the RRT* connection phase, a bidirectional search strategy is introduced to boost the planning speed of the RRT* algorithm. Simultaneously, path pruning is implemented to eliminate redundant nodes and optimize path quality. Finally, comparisons are made with the RRT*, Bi-RRT*, Bias-RRT*, Bias-P-RRT*, and Informed-RRT* algorithms in seven different environments, including comparative data and analysis, validating the feasibility and superiority of the new optimization algorithm. Through comparison, the new algorithm demonstrates significant improvements, it yields shorter and smoother path lengths compared to other algorithms. In seven environments, it maintains a 100% success rate, reducing the required time by at least 40%. Overall, it exhibits superior path quality, enhanced adaptability to varying environments, and ultra-high speed.

关键词： Path planning Direction-biased variable-step-size RRT

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An all-digital low-complexity blind background calibration of timing mismatch in time-interleaved ADCs

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MICROELECTRONICS JOURNAL 2024年 151卷

作者： Zhong, Wei Lang, Lili Dong, Yemin Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol State Key Lab Mat Integrated Circuits 865 Changning Rd Shanghai 200050 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Univ Chinese Acad Sci Ctr Mat Sci & Optoelect Engn Beijing 100049 Peoples R China

This paper proposed a novel all-digital blind background calibration to mitigate timing mismatch in timeinterleaved analog-to-digital converter (TIADC). In estimation module, the adoption of a subtraction-based error extraction function and the design of variable-step-size Least Mean Squares algorithm contribute to reducing the computational complexity and enhancing the convergence speed with optimal output accuracy respectively. In compensation module, a dual-stage Taylor series expansion structure has been introduced to effectively maintain the overall output performance. The proposed architecture is applied to a 12-bit 3 GS/s fourchannel TIADC model. Its effectiveness for single-tone and multi-tone signals is proven through systematical testing and analysis. The simulation results exhibit that the Spurious Free Dynamic Range is significantly improved by 54.53 dB in the single-tone signal case, and the timing mismatch is converged after 1000 samples. The proposed calibration circuit has been synthesized utilizing a 28 nm standard cell library for assessing its hardware consumption, area (0.051 mm(2)) and average power dissipation (67.5 mW) within the integrated chip architecture. Our technology provides a viable optimization solution to improve efficiency of TIADC in highspeed systems.

关键词： All-digital calibration TIADC Timing mismatch variable-step-size Dual-stage Taylor series

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variable step-size subband backward BSS algorithms for speech quality enhancement

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APPLIED ACOUSTICS 2014年第Dec.期86卷 25-41页

作者： Bendoumia, Redha Djendi, Mohamed Univ Saad Dahlab Blida Signal Proc & Image Lab LATSI Blida 09000 Algeria

This paper addresses the problem of the speech quality improvement using adaptive filtering algorithms. Recently in Djendi and Bendoumia (2014)[1], we have proposed a new two-channel backward algorithm for noise reduction and speech intelligibility enhancement. The main drawback of proposed two-channel subband algorithm is its poor performance when the number of subband is high. This inconvenience is well seen in the steady state regime values. The source of this problem is the fixed step-sizes of the cross-adaptive filtering algorithms that distort the speech signal when they are selected high and degrade the convergence speed behaviours when they are selected small. In this paper, we propose four modifications of this algorithm which allow improving both the convergence speed and the steady state values even in very noisy condition and a high number of subbands. To confirm the good performance of the four proposed variable-step-size SBBSS algorithms, we have carried out several simulations in various noisy environments. In these simulations, we have evaluated objective and subjective criteria as the system mismatch, the cepstral distance, the output signal-to-noise-ratio, and the mean opinion score (MOS) method to compare the four proposed variables step-size versions of the SBBSS algorithm with their original versions and with the two-channel fullband backward (2CFB) least mean square algorithm. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Subband backward structure variable-step-size Speech quality Speech enhancement System mismatch Speech-to-noise ratio Two-channel mixing model Mean opinion score

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Least mean p-power algorithms with generalized correntropy

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SIGNAL PROCESSING 2021年 185卷 108058-108058页

作者： Li, Guoliang Zhang, Hongbin Wang, Gang Huang, Fuyi Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Peoples R China Guangxi Univ Comp Elect & Informat Nanning 530004 Peoples R China

A family of least mean p-power (LMP) algorithms including the sign algorithm (SA, p = 1 ), the least mean square (LMS, p = 2 ) and the LMP ( 1 < p < 2 ), have been widely applied in system identification because of their advantages for easy implementation. In some application systems on the basis of sparse features, the generalized correntropy (GC) which is a good measure to address sparse problem, is applied to these LMP-type algorithms in order to improve algorithms' performance with response to convergence rate or filtering accuracy. And the LMP-type algorithms with GC are proposed in this paper, called as GCSA, GCLMS and GCLMP respectively. In addition, simplified versions of these proposed algorithms (written as SGCSA, SGCLMS and SGCLMP) are also derived to save lots of computations. To overcome the limitation of fixed step size in filtering precision and convergence speed, a variable-step-size method is derived. Furthermore, the convergence of proposed algorithms are analysed. For white input signals, simulation results are demonstrated to verify the good performance of proposed algorithms. (c) 2021 Published by Elsevier B.V.

关键词： Least mean p-power (LMP) algorithms System identification Sparse Generalized correntropy variable-step-size

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New efficient two channel forward set-membership partial-update NLMS algorithms for blind speech enhancement and acoustic noise reduction

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APPLIED ACOUSTICS 2018年 141卷 322-332页

作者： Cheffi, Abdelhak Djendi, Mohamed Guessoum, Abderrezak Univ Blida 1 Lab Signal Proc & Imaging LATSI Route SoumaaBP 270 Blida 09000 Algeria

This paper addresses the problem of speech enhancement by partial adaptive algorithms combined with the forward blind source separation (FBSS) structure. We propose three new two-channel forward partial update algorithms: (i) The first algorithm is based on the use of the correlation properties to adapt and control the variable step-size parameter of adaptive cross-filters of the FBSS structure, this algorithm is called the two channel correlated set membership partial update NLMS (TC-SM-PU-NLMScor). (ii) The second algorithm is based on the use of a new coefficients update relations to control the normalization energy of the adaptive NLMS cross filters of the FBSS structure. This algorithm is called the two channel set member ship partial update regularized NLMS (TC-SM-PU-RNLMS). (iii) The third algorithm is a combination of proposed 1 (TC-SM-PU-NLMScor) and proposed 2 (TC-SM-PU-RNLMS), this algorithm is called the two channel correlated set membership partial update regularized NLMS (TC-SM-PU-RNLMScor). In this paper, we show the obtained results of the comparison between the three proposed algorithms and the original two channel correlated set membership partial NLMS (TC-SM-PU-NLMS) algorithm. This comparison is expressed in terms of objective criteria as the System Mismatch (SM), the Segmental Mean Square Error (SegMSE) and the Segmental SNR (SegSNR).

关键词： Speech enhancement Adaptive algorithm Convergence speed variable-step-size Correlation MSE

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