A Fractional-Order Adaptive Filtering Algorithm in Impulsive Noise Environments

Luo, Yongjiang; Yang, Jiali; Zhang, Qiang; Wang, Changlong

doi:10.1109/tcsii.2021.3073961

Cited by 11 publications

(1 citation statement)

References 19 publications

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“…There are many marine organisms, such as snapping shrimp, that can emit impulsive noise [11], which causes underwater acoustic channels to be frequently affected by impulsive noise. To make adaptive algorithms more robust under impulsive noise conditions, the least mean p-power (LMP) algorithm is often used to replace the least mean square algorithm [12][13][14]. Xiong K et al, aiming to improve the robustness of adaptive algorithms in the presence of non-linear interference, utilized the minimum average p-norm as a replacement for the traditional minimum mean square error algorithm to upgrade the algorithm.…”

Section: Introductionmentioning

confidence: 99%

A Convex Combination–Variable-Step-Size Least Mean p-Norm Algorithm

Zhu,

Wang,

Cai

et al. 2024

Electronics

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Underwater acoustic channels often have to face the interference of impulsive noise, which is usually modeled by α-stable distribution in simulation experiments. To solve the problem of underwater acoustic channel estimation under impulsive noise, this paper proposes a convex combination–variable-step-size least mean p-norm algorithm. The algorithm incorporates a convex combination into the variable-step-size least mean p-norm algorithm and uses the convex combination of different convergence domains provided by changing the parameters of the Gaussian function to further improve the effect after convergence. The simulation results of channel estimation show that the convex combination–variable-step-size least mean p-norm algorithm provides a more stable, robust, and universal solution than the variable-step-size least mean p-norm algorithm.

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