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Filtered-X affine projection algorithm for multichannel active noise control using second-order volterra filters

IEEE SIGNAL PROCESSING LETTERS 2004年第11期11卷 853-857页

作者： Sicuranza, GL Carini, A Univ Trieste DEEI I-34127 Trieste Italy Univ Urbino Ist Sci & Tecnol I-61029 Urbino Italy

In this letter, a multichannel controller based on Volterra filters is described. A filtered-X affine projection algorithm is derived in detail for homogeneous quadratic filters. The proposed algorithm can be also ext... 详细信息

关键词： active noise control adaptive Volterra filters affine projection algorithm multichannel nonlinear controller

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On the Convergence Behavior of the affine projection algorithm for Adaptive Filters

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2011年第8期58卷 1813-1826页

作者： Paul, Thomas K. Ogunfunmi, Tokunbo Santa Clara Univ Dept Elect Engn Santa Clara CA 95053 USA

The affine projection class of algorithms (APA) provides faster convergence than LMS-based adaptive filters. Its convergence analysis is not as extensively studied as Normalized LMS (NLMS), and remains an active area of research. For tractability, most works on APA make many assumptions on the statistics of the input, as well as correlation between signals. Here we consider the effect of the correlation between filter coefficients and past measurement noise on MSE error. The effect of this correlation was found to be dependent on step-size mu, increasing or decreasing the predicted MSE depending on whether mu is less than or greater than 1, irrespective of the input statistics. Simulations are used to verify the analysis results presented.

关键词： Adaptive filters affine projection algorithm APA mean-square error misadjustment steady-state analysis

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A New affine projection algorithm and Its Statistical Behavior

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CHINESE JOURNAL OF ELECTRONICS 2013年第3期22卷 537-542页

作者： Zhi Yongfeng Li Ru Li Huxiong Northwestern Polytech Univ Dept Automat Control Xian 710072 Peoples R China

An affine projection algorithm with Direction error (AP-DE) is presented by redefining the iteration error. Under a measurement-noise-free condition, the iteration error is directly caused by the direction vector. A statistical analysis model is used to analyze the AP-DE algorithm. Deterministic recursive equations for the mean weight error and for the Mean-square error (MSE) in iteration direction are derived. We also analyze the stability of MSE in iteration direction and the optimal step-size for the AP-DE algorithm. Simulation results are provided to corroborate the analytical theory.

关键词： Adaptive filters affine projection algorithm Statistical analysis Iteration direction

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An Efficient Norm Constraint Memory Improved Proportionate affine projection algorithm

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2017年第8期36卷 3448-3456页

作者： Qu, Zhaoxia Zheng, Zongsheng Lanzhou Univ Technol Sch Sci Lanzhou Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China

This paper proposes an norm constraint memory improved proportionate affine projection algorithm with a lower computational complexity than the conventional norm constraint improved proportionate affine projection algorithm. Particularly, to achieve a low computational complexity, we propose to remove the matrix before the zero attraction term. Moreover, the product of the proportionate matrix and input matrix is implemented using an efficient recursive scheme. Simulation results in acoustic echo cancellation context show that our algorithm not only significantly reduces the computational complexity but also achieves slightly improved steady-state misalignment.

关键词： affine projection algorithm Sparse impulse response Efficient recursive implementation Acoustic echo cancellation

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Set-membership affine projection algorithm based on the percentage change of the error signal and variable projection order

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IEEE LATIN AMERICA TRANSACTIONS 2022年第3期20卷 496-502页

作者： Trejo, Carlos Maya, Xochitl Martinez, Rene Sanchez, Gabriel Perez, Hector Avalos, Juan Sanchez, Giovanny Inst Politecn Nacl ESIME Mexico City DF Mexico

Nowadays, the use of adaptive filters plays an important role in multiple signal processing applications, such as active noise control, acoustic echo cancellers, system identifiers, channel equalizer, among others. Until date, many of the existing adaptive algorithms such as affine projection algorithms offer a high convergence speed. However, its computational cost is also high. Currently, several authors make extraordinary efforts to reduce its computational cost to be used in practical applications. In this paper, we propose a new set-membership affine projection algorithm based on the percentage change of the error signal and variable projection order (SMAP-PC-VO). Specifically, we propose two techniques to create this algorithm;1) the new algorithm uses an error bound, which is obtained by calcuting the percentage change of the error signal, to avoid the computation of the variance of additive noise, since in existing approaches this parameter determines the error bound. In practical applications, the computation of the variance of additive noise is infeasible since this signal is not available;2) we propose a new method to dynamically modify the projection order in the new algorithm. As a consequence, its computational cost is reduced. To demonstrate its performance, the proposed algorithm was successfully tested in different environments for system identification and active noise control for headphone applications. The simulation results demonstrate that the proposed algorithm presents good convergence properties. In addition, the proposed algorithm exhibits a low overall computational complexity.

关键词： projection algorithms Signal processing algorithms Internet of Things Computational efficiency IEEE transactions Heuristic algorithms Convergence set-membership algorithm affine projection algorithm data selective algorithms variable projection order

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affine projection algorithm by Employing Maximum Correntropy Criterion for System Identification of Mixed Noise

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IEEE ACCESS 2019年 7卷 182515-182526页

作者： Wang, Xiaoding Han, Jun Zhejiang Univ Ocean Coll Hangzhou 310027 Peoples R China

The adaptive algorithms have been widely studied in Gaussian environment. However, the impulsive noise and other non-Gaussian noise may largely deteriorate the performance of algorithm in practical applications. To address this problem, in this paper, we propose two novel adaptive algorithms for system identification problem with mixed noise scenarios. Both proposed algorithms are based on the framework of the affine projection (AP) algorithm. The first proposed algorithm, termed as VS-APMCCA, combines variable step-size (VS) strategy and maximum correntropy criterion (MCC) to obtain improved performance. For further performance improvement, the VC-VS-APMCCA is developed, which is based on the variable center (VC) scheme of MCC. The convergence analysis of the VC-VS-APMCCA is conduced. Finally, simulation results demonstrate the superior performance of the VS-APMCCA and VC-VS-APMCCA.

关键词： affine projection algorithm variable step-size maximum correntropy criterion (MCC) variable center (VC) mixed noise

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A Variable Regularization Method for affine projection algorithm

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2010年第6期57卷 476-480页

作者： Yin, Wutao Mehr, Aryan Saadat Univ Saskatchewan Dept Elect & Comp Engn Saskatoon SK S7N 5A9 Canada

The affine projection algorithm (APA) is a generalization of the normalized least mean square algorithm. We propose a variable regularization factor for the APA. Instead of the conventional assumption that the a posteriori error is zero, we incorporate the statistical characteristic of the noise into the adaptation process based on a system identification setup. Exact and approximate formulations for the optimal regularization factor are derived. Numerical simulation results show that the proposed algorithm improves the performance of the APA in terms of its convergence rate and steady-state misalignment.

关键词： Adaptive filtering affine projection algorithm variable regularization

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Blind adaptive affine projection algorithm-based multiuser detector over a multipath fading channel

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SIGNAL PROCESSING 2010年第6期90卷 2102-2106页

作者： Zhang, Daoming Wang, Kun Zhang, Xianda Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

In this paper, we propose a novel blind adaptive multiuser detector based on the affine projection algorithm (APA) for asynchronous direct-sequence code-division multiple-access (DS-CDMA) systems over a multipath fading channel. Computational complexities of least mean-squares (LMS), Kalman filter and APA-based blind adaptive multiuser detector are compared. The proposed detector is shown to outperform the LMS detector and has similar convergence and detection properties as the Kalman filtering with much reduced computation cost. (C) 2009 Elsevier B.V. All rights reserved.

关键词： affine projection algorithm Blind multiuser detection Code-division multiple-access (CDMA) Multipath fading channel

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A robust variable step-size affine projection algorithm

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SIGNAL PROCESSING 2010年第9期90卷 2806-2810页

作者： Vega, Leonardo Rey Rey, Hernan Benesty, Jacob Univ Buenos Aires Fac Ingn Buenos Aires DF Argentina Consejo Nacl Invest Cient & Tecn RA-1033 Buenos Aires DF Argentina Univ Quebec INRS EMT Montreal PQ H5A 1K6 Canada

We present a robust variable step-size affine projection algorithm (RVSS-APA) using a recently introduced new framework for designing robust adaptive filters. The algorithm is the result of minimizing the square norm of the a posteriori error vector subject to a time-dependent constraint on the norm of the filter update. The RVSS-APA is then successfully tested in different environments for system identification and acoustic echo cancellation applications. (C) 2010 Elsevier B.V. All rights reserved.

关键词： System identification affine projection algorithm Impulsive noise Robust filtering Acoustic echo cancellation

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Steady-state weights solution to affine projection algorithm

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控制理论与应用（英文版） 2012年第2期10卷 259-263页

作者： Yongfeng Zhi Jun Zhang Yinxue Li Department of Automatic Control Northwestern Polytechnical University Xi'an Shaanxi 710072 China

A new expression of the weights update equation for the affine projection algorithm （APA） is proposed that improves the convergence rate of an adaptive flter, particularly for highly colored input signals, and yields greater details of the internal structure. The steady-state weights solution to the APA algorithm is calculated in different step-sizes, which is significantly different from the iteration method. The weights error in steady-state is proved to be zero as the number of the input direction vector increases to infinity, ensuring that the estimated weights of the APA algorithm in steady-state are unbiased and consistent. The sensitivity of the step-size parameter for the steady-state weights is also analyzed. Simulation results show that the steady-state weights of the APA algorithm, obtained from the proposed method, are closer to the true weights than the estimated steady-state weights as determined by the traditional iteration method.

关键词： affine projection algorithm Steady-state Identification Adaptive filtering

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