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IEEE International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

作者： Ibarra, I. Rodriguez, J. Pichardo, E. Avalos, J. G. Avalos, G. Inst Politecn Nacl ESIME Culhuacan Mexico City DF Mexico

ISBN: (纸本)9781538691915

affine projection (AP) algorithms offer a relatively good convergence speed which can be increased by augmenting the projection order (L), however, in addition to presenting a high computational complexity, their steady-state misadjustment worsens in direct ratio to the rise of L. Convex combinations of AP algorithms have been devised in an attempt to address the misadjustment issue, albeit at the cost of doubling the aforementioned computational complexity. This work introduces the convex combination of an AP algorithm with an Error Coded Least Mean Square (ECLMS) algorithm, in order to reduce the twofold increase in computational complexity of dual AP combinations while retaining the high convergence speed and improving the steady-state misadjustment level. The proposed algorithm was tested in a system identification application, results demonstrate that the proposal performs as good or better than dual AP solutions, while considerably reducing computational complexity.

关键词： Adaptive filters Convex combination affine projection algorithm Error coded least mean square

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Linear phase sparse system identification in the presence of impulsive noise

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International Journal of Electronics Letters 2019年第3期7卷 321-337页

作者： Yadav, Rajni Rai, C.S. University School of Information Communication and Technology Guru Gobind Singh Indraprastha University Delhi India

In this paper, we incorporate an ℓp-norm sparsity constraint into linear phase constrained affine projection-sign algorithm (LPCAP-SA). The proposed algorithm combines the effect of linear phase constrained affine pro... 详细信息

In this paper, we incorporate an ℓ_p-norm sparsity constraint into linear phase constrained affine projection-sign algorithm (LPCAP-SA). The proposed algorithm combines the effect of linear phase constrained affine projection sign algorithm and ℓ_p-norm sparsity *** proposed algorithm has better performance for linear phase sparse system identification in the presence of vigorous impulsive interference. The proposed ℓ_p-norm LPCAP-SA is based on the ℓ₁-norm minimisation criterion on posterior error and ℓ_p-Norm on weight coefficients and a linear phase constraint. Simulations in Matlab software show that the proposed ℓ_p-norm LPCAP-SA has robustness against impulsive interferences and sparse environment for linear phase system. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

关键词： affine projection algorithm impulsive interference Linearly constrained adaptive filter sign algorithm sparsity ℓp-norm

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A novel adaptive active noise control algorithm based on Tikhonov regularisation 10

A novel adaptive active noise control algorithm based on Tik...

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10th International Conference on Signal Processing Systems (ICSPS)

作者： Ardekani, Iman Sakhaee, Neda Sharifzadeh, Hamid Barmada, Bashar Lovell, Gerard Unitec Inst Technol Auckland New Zealand Univ Auckland Auckland New Zealand

ISBN: (数字)9781510628366

ISBN: (纸本)9781510628366

This paper proposes a novel adaptive active noise control algorithm based on Tikhonov regularization theory. A regularized cost function consisting of the weighted sum of the most recent samples of the residual noise and its derivative is defined. By setting the gradient vector of the cost function to zero, an optimal solution for the control parameters is obtained. Based on the proposed optimal solution, a computationally efficient algorithm for adaptive adjustment of the control parameters is developed. It is shown that the regularized affine projection algorithm can be considered as a very special case of the proposed algorithm. Different computer simulation experiments show the validity and efficiency of the proposed algorithm.

关键词： active noise control adaptive algorithms Tikhonov regularization affine projection algorithm

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Novel affine projection Sign Subband Adaptive Filter 3rd

Novel Affine Projection Sign Subband Adaptive Filter

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3rd International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT)

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

ISBN: (纸本)9789811079863;9789811079856

In this paper, we propose a novel affine projection sign subband adaptive filter (NAPSSAF) algorithm which can obtain better performance than the conventional APSSAF. The proposed NAPSSAF is derived by minimizing the l1-norm of the subband a posteriori error vector rather than the overall a posteriori error vector, which fully uses the subband adaptive filter's inherent decorrelating property. Simulations in context of the system identification and acoustic echo cancellation (AEC) are carried out to demonstrate the advantages of the proposed algorithms. The results of simulations demonstrate that the proposed NAPSSAF obtains faster convergence rate than the existing algorithms.

关键词： Normalized subband adaptive filter affine projection algorithm Acoustic echo cancellation (AEC)

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affine projection algorithm with Variable projection Order

Affine Projection Algorithm with Variable Projection Order

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IEEE International Conference on Communications

作者： Reza Arablouei Kutluyil Dogancay Institute for Telecommunications Research University of South Australia School of Electrical and Information Engineering University of South Australia

ISBN: (纸本)9781457720529

Increasing the projection order in the affine projection adaptive filtering algorithm speeds up the convergence but also increases the steady-state misalignment. To address this unfavorable compromise, we propose a new affine projection algorithm with a variable projection order. This algorithm adaptively changes the projection order according to the estimated variance of the filter output error. The error variance is estimated using the exponential window and moving averaging techniques and employing a variable forgetting factor. Simulations demonstrate that the new algorithm provides fast initial convergence and low steady-state misalignment without necessarily trading off one for the other in addition to a significant reduction in average computational complexity.

关键词： Adaptive filtering affine projection algorithm Variable projection order Error variance estimation

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An affine projection algorithm based DFE with set-membership filtering

An affine projection algorithm based DFE with set-membership...

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International Conference on Computers and Devices for Communication (CODEC)

作者： Ramesh Chandra Mishra Ratnajit Bhattacharjee Abhijit Mitra Department of EEE Indian Institute of Technology Guwahati Assam India Department of ECE Sir J. C. Bose School of Engineering West Bengal India

ISBN: (纸本)9781467326193

A channel equalization technique based on the affine projection algorithms (APA) with set-membership (SM) filtering for updating filters of a decision feedback equalizer (DFE) is proposed for time-varying wireless channels. The performance of the proposed approach is analyzed through simulations. It is shown in the results that this scheme offers advantages of having substantial fewer number of weight updating operations at moderate SNR with almost similar convergence as normal APA based equalizer. The introduced equalizer converges faster with a marginal increase in complexity than the set-membership normalized least mean square (NLMS) algorithm based equalizer.

关键词： affine projection algorithm Decision feedback equalizer Normalized least mean square algorithm Set-membership decision feedback equalisers projection algorithms Least mean square algorithm Equalizers HELIOS DEVICES Filtration ALASKA POWER ADMINISTRATION based

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ZA-APA with zero attractor controller selection criterion for sparse system identification

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SIGNAL IMAGE AND VIDEO PROCESSING 2018年第2期12卷 371-377页

作者： Radhika, S. Sivabalan, A. Sathyabama Univ Madras Tamil Nadu India

The zero attraction affine projection algorithm (ZA-APA) is one of the sparse APAs that are based on -norm penalty function. It provides faster convergence and lower steady-state error than the conventional APA when the system is sparse. Most of the analysis for attraction-type APA is normally based on white Gaussian assumption for the input. In this paper, a detailed performance analysis of the ZA-APA is performed using individual weight error variance (IWV) method. Using the IWV method, the condition for the convergence in mean and mean square error sense and the steady-state mean square deviation (MSD) error based on non-Gaussian input assumption is derived. Theoretical derivation reveals that the value of zero attractor controller plays a key role in the final steady-state error. Hence, a selection criterion for zero attractor controller based on the steady-state MSD error is proposed. Finally, simulations are performed to validate the analysis made in the context of unknown system identification.

关键词： affine projection algorithm Zero attraction APA Mean square deviation Convergence Nonzero weights Zero weights Zero attractor controller

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An adaptive convex combination of APA and ZA-APA for identifying systems having variable sparsity and correlated input

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DIGITAL SIGNAL PROCESSING 2018年 82卷 118-132页

作者： Gogineni, Vinay Chakravarthi Das, Bijit K. Chakraborty, Mrityunjoy Indian Inst Technol Dept Elect & Elect Commun Engn Kharagpur W Bengal India

In this paper, we present an efficient algorithm for identifying and tracking the impulse response of a sparse system that exhibits time varying sparseness and is driven by correlated input. The proposed method convexly combines the outputs of two filters, namely, the sparsity unaware affine projection algorithm (APA), and the sparsity aware zero attracting affine projection algorithm (ZA-APA), each trying to identify the same system using the same input. The combining parameter is adapted by following a steepest descent of the error variance at the convex combination output. A detailed performance analysis of the proposed combination is carried out, which reveals that while for highly non-sparse and highly sparse systems, the proposed combination converges respectively to the APA and ZA-APA (i.e., better of the two filters under the given levels of sparsity), for certain sparsity ranges, it leads to a combination filter that performs better than both the constituent filters. The claims made are validated by exhaustive simulation studies using white, colored as well as speech inputs. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Sparse systems l(1)-norm Excess mean square error Adaptive filter affine projection algorithm

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Analysis of affine projection Normalized Correlation algorithm

Analysis of Affine Projection Normalized Correlation Algorit...

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International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Koike, Shin'ichi Tokyo Japan

ISBN: (纸本)9781509006298

This paper proposes and develops a statistical analysis of affine projection Normalized Correlation algorithm (AP-NCA) which is a combination of the affine projection algorithm (APA) and Normalized Correlation algorithm (NCA) for use in complex-domain adaptive filters. For impulse noise, two types are considered: one is found in observation noise and another at filter input. Through experiments with simulations and theoretical calculations of filter convergence, we demonstrate that the proposed AP-NCA is effective in making adaptive filters converge faster when the filter inputs are correlated, and robust in impulsive noise environments. It is observed that the theoretical convergence curves generally exhibit good agreement with the simulation results which shows that the analysis is valid for practical use.

关键词： adaptive filter affine projection algorithm normalized correlation algorithm impulse noise fast convergence robust filtering

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A Theory on the Convergence Behavior of the affine projection algorithm

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第12期59卷 6233-6239页

作者： Kim, Seong-Eun Lee, Jae-Woo Song, Woo-Jin Pohang Univ Sci & Technol POSTECH Educ Inst Future Informat Technol Pohang 790784 South Korea Pohang Univ Sci & Technol POSTECH Div Elect & Comp Engn Pohang 790784 South Korea

In this paper, we present a theoretical convergence analysis of the affine projection algorithm (APA) based on the arguments of energy conservation. Although the APA and its convergence analysis have been widely studied, the dependency of weight-error vector on past noise is usually neglected for simplicity. To obtain accurate theoretical results for the APA, we here consider the dependency between the weight-error vector and past noise in the mean-square analysis presented by Shin and Sayed in ["Mean-square performance of a family of affine projection algorithms," IEEE Transactions on Signal Processing, vol. 52, no. 1, pp. 90-102, January 2004]. Through this work, we can also theoretically analyze the behavior of the periodic APA, which updates its weights periodically. Simulation results show that our theoretical results coincide closely with simulations.

关键词： Adaptive filter affine projection algorithm energy-conservation mean-square performance analysis

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