Affine projection mixed-norm algorithms for robust filtering

Li, Guo Liang; Gang, Wang; Dai, Yaru; Sun, Qing; Yang, Xinyue; Zhang, Hongbin

doi:10.1016/j.sigpro.2021.108153

Cited by 17 publications

(2 citation statements)

References 34 publications

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“…The results indicate that the algorithm exhibits a fast convergence rate in environments with a low pulse intensity (α = 1.7). By integrating the AP algorithm with other methods, Li proposed two novel adaptive approaches for addressing impulsive noise [59]. Zhao presented a multi-convex combination maximum correntropy adaptive algorithm.…”

Section: Other Transformation Algorithmsmentioning

confidence: 99%

Review of Advances in Active Impulsive Noise Control with Focus on Adaptive Algorithms

Liu,

Lei

2024

Applied Sciences

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Mitigating low-frequency noise in various industrial applications often involves the use of the filter-x least mean squares (FxLMS) algorithm, which relies on the mean square error criterion. This algorithm has demonstrated effectiveness in reducing noise induced by Gaussian noise within noise control systems. However, the performance of this algorithm experiences significant degradation and does not converge properly in the presence of impulsive noise. Consequently, to uphold the stability of the ANC system, several robust adaptive algorithms tailored to handle shock noise interference have been introduced. This paper systematically organizes and classifies robust adaptive algorithms designed for impulse noise based on algorithmic criteria, offering valuable insights for the research and application of pertinent active impact noise control methods.

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Section: Other Transformation Algorithmsmentioning

confidence: 99%

Review of Advances in Active Impulsive Noise Control with Focus on Adaptive Algorithms

Liu,

Lei

2024

Applied Sciences

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“…Representative adaptive filtering algorithms include the least-mean-squares (LMS) algorithm and normalized LMS algorithm, which have a low computational complexity and can be easily implemented. In addition, the affine projection algorithm (APA) [7][8][9] has been developed to enhance the convergence performance associated with correlated input signals. However, because LMS-type and APA-type algorithms are based on the L 2 -norm optimization of error signals, their performance deteriorates in the presence of system output noise, which includes impulsive noise.…”

Section: Introductionmentioning

confidence: 99%

ℒp-Norm-like Affine Projection Sign Algorithm for Sparse System to Ensure Robustness against Impulsive Noise

Shin

Kim

et al. 2021

Symmetry

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An improved affine projection sign algorithm (APSA) was developed herein using a ℒp-norm-like constraint to increase the convergence rate in sparse systems. The proposed APSA is robust against impulsive noise because APSA-type algorithms are generally based on the ℒ1-norm minimization of error signals. Moreover, the proposed algorithm can enhance the filter performance in terms of the convergence rate due to the implementation of the ℒp-norm-like constraint in sparse systems. Since a novel cost function of the proposed APSA was designed for maintaining the similar form of the original APSA, these have symmetric properties. According to the simulation results, the proposed APSA effectively enhances the filter performance in terms of the convergence rate of sparse system identification in the presence of impulsive noises compared to that achieved using the existing APSA-type algorithms.

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Recursive constrained generalized maximum correntropy algorithms for adaptive filtering

Zhao

Zhang

et al. 2022

Signal Processing

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Affine projection mixed-norm algorithms for robust filtering

Cited by 17 publications

References 34 publications

Review of Advances in Active Impulsive Noise Control with Focus on Adaptive Algorithms

Review of Advances in Active Impulsive Noise Control with Focus on Adaptive Algorithms

ℒp-Norm-like Affine Projection Sign Algorithm for Sparse System to Ensure Robustness against Impulsive Noise

Recursive constrained generalized maximum correntropy algorithms for adaptive filtering

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