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Robust Set-Membership affine projection algorithm with Coefficient Vector Reuse

CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2017年第9期36卷 3843-3853页

作者： Zheng, Zongsheng Zhao, Haiquan Minist Educ Key Lab Magnet Suspens Technol & Maglev Vehicle Chengdu Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China

This paper proposes a robust set-membership affine projection algorithm with coefficient vector reuse (RSM-APA-CVR) for high background noise environment. In the proposed algorithm, the sum of the squared norms of the differences between the updated weight vector and past weight vectors is minimized and a new robust error bound is designed. Simulation results in acoustic echo cancellation context show that the proposed algorithm has faster convergence rate and smaller steady-state misalignment as compared to the conventional RSM-APA.

关键词： affine projection algorithm Set-membership Coefficient vector reuse Acoustic echo cancellation High background noise Impulsive noise

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Steady-State Mean Square Performance of the Multichannel Filtered-X affine projection algorithm

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2012年第6期60卷 2771-2785页

作者： Ferrer, Miguel de Diego, Maria Gonzalez, Alberto Pinero, Gema Univ Politecn Valencia Inst Telecommun & Multimedia Applicat iTEAM E-46071 Valencia Spain

This paper provides a unified analysis of the steady-state behavior of different multichannel filtered-x affine projection algorithms when used in active noise control (ANC) systems. The analysis deals with two different filtering schemes: the modified filtered-x affine projection (MFXAP) algorithm, with the modified filtered-x structure embedded, that has been studied in previous works, and the filtered-x affine projection (CFXAP) algorithm, with the conventional filtered-x structure embedded, that becomes the main contribution of this work. This study is based on energy conservation principles and does not require a specific signal distribution. The derived theoretical models allow to accurately predict the steady-state performance of the considered algorithms for moderate AP orders and low step sizes mu. Simulation results obtained in practical ANC systems validate both the analysis and the achieved expressions, showing a relative good match between theory and practice.

关键词： Active noise control (ANC) affine projection algorithm energy conservation filtered-x structure multichannel adaptive filtering steady-state analysis

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An efficient affine projection algorithm for 2-D FIR adaptive filtering and linear prediction

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SIGNAL PROCESSING 2006年第1期86卷 98-116页

作者： Glentis, GO Technol Educ Inst Crete Branch Chania Dept Elect Khania 73133 Crete Greece

In this paper, a fast affine projection algorithm (FAPA), for the two-dimensional (2-D) adaptive linear filtering and prediction, is presented. The derivation of the proposed algorithm is based on the spatial shift-invariant properties of the 2-D discrete time signals. The proposed algorithm has low computational complexity, comparable to that of the 2-D LMS algorithm. The performance of the proposed scheme is comparable to that of the higher complexity 2-D RLS algorithms. The convergence speed and the tracking ability of the proposed 2-D FAPA algorithm are illustrated by computer simulation. (c) 2005 Elsevier B.V. All rights reserved.

关键词： two-dimensional adaptive filtering fast least-squares algorithms affine projection algorithm

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Distributed affine projection algorithm Over Acoustically Coupled Sensor Networks

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2017年第24期65卷 6423-6434页

作者： Ferrer, Miguel Gonzalez, Alberto de Diego, Maria Pinero, Gema Univ Politecn Valencia Inst Telecommun & Multimedia Applicat E-46022 Valencia Spain

In this paper, we present a distributed affine projection (AP) algorithm for an acoustic sensor network where the nodes are acoustically coupled. Every acoustic node is composed of a microphone, a processor, and an actuator to control the sound field. This type of networks can use distributed adaptive algorithms to deal with the active noise control (ANC) problem in a cooperative manner, providing more flexible and scalable ANC systems. In this regard, we introduce here a distributed version of the multichannel filtered-x AP algorithm over an acoustic sensor network that it is called distributed filtered-x AP (DFxAP) algorithm. The analysis of the mean and the mean-square deviation performance of the algorithm at each node is given for a network with a ring topology and without constraints in the communication layer. The theoretical results are validated through several simulations. Moreover, simulations show that the proposed DFxAP outperforms the previously reported distributed multiple error filtered-x least mean square algorithm.

关键词： Acoustic sensor networks affine projection algorithm distributed adaptive filters active noise control

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Statistical tracking behavior of affine projection algorithm for unity step size

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APPLIED MATHEMATICS AND COMPUTATION 2016年 283卷 22-28页

作者： Zhi, Yongfeng Yang, Yunyi Zheng, Xi Zhang, Jun Wang, Zhen Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China

Since unity step size could guarantee the fastest convergence and more detailed analysis for the affine projection (AP) algorithm, a statistical tracking behavior of AP algorithm is discussed in this paper. Deterministic recursive equations are derived for the mean weight error and mean-square error. All the possible correlations between the adaptive filtering coefficients and the past measurement noise are considered as well. (c) 2016 Elsevier Inc. All rights reserved.

关键词： affine projection algorithm Tracking behavior System identification Step size

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A Variable Step-Size Shrinkage Set-Membership affine projection algorithm for Noisy Input

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2019年第1期38卷 455-469页

作者： Yin, Kaili Zhao, Haiquan Southwest Jiaotong Univ Sch Elect Engn Chengdu Sichuan Peoples R China Minist Educ Key Lab Magnet Suspens Technol & Maglev Vehicle Chengdu Peoples R China

To solve the conflicting requirement of fast convergence and low steady-state misalignment, a variable step-size shrinkage set-membership affine projection algorithm is proposed, which is efficient for the correlated input signal and noisy input environments. The new variable step size is derived by minimizing the square of noise-free a posteriori error, and the shrinkage method is employed to estimate the second-order statistics of the noise-free a priori error vector. Moreover, the stability analysis of the algorithm is conducted. Simulations demonstrate the effectiveness of the proposed algorithm for various noisy input environments.

关键词： Noisy input affine projection algorithm Variable step size Shrinkage Echo cancelations

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Variable matrix-type step-size affine projection algorithm with orthogonalized input vectors

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SIGNAL PROCESSING 2014年 98卷 135-142页

作者： Park, PooGyeon Seo, Ji-Hye Kong, NamWoong Pohang Univ Sci & Technol Dept Elect Engn Pohang 790784 Gyungbuk South Korea Pohang Univ Sci & Technol Div Informat Technol Convergence Engn Pohang 790784 Gyungbuk South Korea POSCO Pohang Gyungbuk South Korea

In this paper, we propose a variable matrix-type step-size affine projection algorithm (APA) with orthogonalized input vectors. We generate orthogonalized input vectors using the Gram-Schmidt process to implement the weight update equation of the APA using the sum of normalized least mean squares (NLMS)-like updating equations. This method allows us to use individual step sizes corresponding to each NLMS-like equation, which is equivalent to adopting the step size in the form of a diagonal matrix in the APA. We adopt a variable step-size scheme, in which the individual step sizes are determined to minimize the mean square deviation of the APA in order to achieve the fastest convergence on every iteration. Furthermore, because of the weight vector updated successively only along each innovative one among the reused inputs and effect of the regularization absorbed into the derived step size, the algorithm works well even for badly excited input signals. Experimental results show that our proposed algorithm has almost optimal performance in terms of convergence rate and steady-state estimation error, and these results are remarkable especially for badly excited input signals. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Adaptive filters affine projection algorithm Gram Schmidt process Variable matrix-type step size MSD analysis Regularization

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An augmented affine projection algorithm for the filtering of noncircular complex signals

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SIGNAL PROCESSING 2010年第6期90卷 1788-1799页

作者： Xia, Yili Took, Clive Cheong Mandic, Danilo P. Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2BT England

An augmented affine projection adaptive filtering algorithm (AAPA), utilising the full second order statistical information in the complex domain is proposed. This is achieved based on the widely linear model and the joint optimisation of the direct and conjugate data channel parameters. The analysis illustrates that the use of augmented complex statistics and widely linear modelling makes the AAPA suitable for the processing of both second order complex circular (proper) and noncircular (improper) signals. The derivation is supported by the analysis of convergence in the energy conservation setting. Simulations on both benchmark and real-world noncircular wind signals support the analysis. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Widely linear modelling affine projection algorithm Complex-valued noncircular signals Augmented complex statistics Wind modelling

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An affine projection algorithm with variable step size and projection order

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DIGITAL SIGNAL PROCESSING 2012年第4期22卷 586-592页

作者： Gonzalez, Alberto Ferrer, Miguel de Diego, Maria Pinero, Gema Univ Politecn Valencia Inst Telecommun & Multimedia Applicat iTEAM Valencia 46022 Spain

It is known that the performance of adaptive algorithms is constrained by their computational cost. Thus, affine projection adaptive algorithms achieve higher convergence speed when the projection order increases, which is at the expense of a higher computational cost. However, regardless of computational cost, a high projection order also leads to higher final error at steady state. For this reason it seems advisable to reduce the computational cost of the algorithm when high convergence speed is not needed (steady state) and to maintain or increase this cost only when the algorithm is in transient state to encourage rapid transit to the permanent regime. The adaptive order affine projection algorithm presented here addresses this subject. This algorithm adapts its projection order and step size depending on its convergence state by simple and meaningful rules. Thus it achieves good convergence behavior at every convergence state and very low computational cost at steady state. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Adaptive filter affine projection algorithm Variable step size Computational cost

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Low Cost Variable Step-Size LMS With Maximum Similarity to the affine projection algorithm

IEEE OPEN JOURNAL OF SIGNAL PROCESSING

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IEEE OPEN JOURNAL OF SIGNAL PROCESSING 2024年 5卷 82-91页

作者： Ferrer, Miguel De Diego, Maria Gonzalez, Alberto Univ Politecn Valencia UPV Inst Telecommun & Multimedia Applicat iTEAM Valencia 46022 Spain

The LMS algorithm is widely employed in adaptive systems due to its robustness, simplicity, and reasonable performance. However, it is well known that this algorithm suffers from a slow convergence speed when dealing with colored reference signals. Numerous variants and alternative algorithms have been proposed to address this issue, though all of them entail an increase in computational cost. Among the proposed alternatives, the affine projection algorithm stands out. This algorithm has the peculiarity of starting from $N$ data vectors of the reference signal. It transforms these vectors into as many data vectors suitably normalized in energy and mutually orthogonal. In this work, we propose a version of the LMS algorithm that, similar to the affine projection algorithm, starts from $N$ data vectors of the reference signal but corrects them by using only a scalar factor that functions as a convergence step. Our goal is to align the behavior of this algorithm with the behavior of the affine projection algorithm without significantly increasing the computational cost of the LMS.

关键词： Signal processing algorithms Convergence projection algorithms Computational efficiency Approximation algorithms Costs Robustness Adaptive filters affine projection algorithm variable step-size

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