New Insights into Convergence Theory of Constrained Frequency-Domain Adaptive Filters

Yang, Feiran; Enzner, Gerald; Yang, Jun

doi:10.1007/s00034-020-01569-6

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…To correctly adjust the step size of the mixing parameter, we also need to consider some characteristics of the filtering scheme, such as input signal and additive noise power, or the step size of the adaptive filter included in the combination [23]. Second, they rarely considered the sparsity of impulse response, resulting in weak robustness of the filters in this situation [24,25].…”

Section: Introductionmentioning

confidence: 99%

Normalized Combinations of Proportionate Affine Projection Sign Subband Adaptive Filter

Zhang

Geng

et al. 2021

Scientific Programming

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The proportionate affine projection sign subband adaptive filter (PAP-SSAF) has a better performance than the affine projection sign subband adaptive filter (AP-SSAF) when we eliminate the echoes. Still, the robustness of the PAP-SSAF algorithm is insufficient under unknown environmental conditions. Besides, the best balance remains to be found between low steady-state misalignment and fast convergence rate. In order to solve this problem, we propose a normalized combination of PAP-SSAF (NCPAP-SSAF) based on the normalized adaption schema. In this paper, a power normalization adaptive rule for mixing parameters is proposed to further improve the performance of the NCPAP-SSAF algorithm. By using Nesterov’s accelerated gradient (NAG) method, the mixing parameter of the control combination can be obtained with less time consumed when we take the l1-norm of the subband error as the cost function. We also test the algorithmic complexity and memory requirements to illustrate the rationality of our method. In brief, our study contributes a novel adaptive filter algorithm, accelerating the convergence speed, reducing the steady-state error, and improving the robustness. Thus, the proposed method can be utilized to improve the performance of echo cancellation. We will optimize the combination structure and simplify unnecessary calculations to reduce the algorithm’s computational complexity in future research.

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Section: Introductionmentioning

confidence: 99%

Normalized Combinations of Proportionate Affine Projection Sign Subband Adaptive Filter

Zhang

Geng

et al. 2021

Scientific Programming

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A Frequency-Domain Output-Constrained Active Noise Control Algorithm Based on an Intuitive Circulant Convolutional Penalty Factor

Shi

Gan

Lam

et al. 2023

IEEE/ACM Trans. Audio Speech Lang. Process.

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A Review of Sound Field Control

Jiang

Han

2022

Applied Sciences

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Sound field control (SFC) technology enables the active management of audio delivered within an acoustical environment. It includes three research directions: sound field reproduction, personal audio systems, and active noise control. Sound field reproduction uses loudspeaker arrays to replicate a sound field in a target region; personal audio systems extend sound field reproduction over multiple regions so that different listeners can hear personalized audio in a shared space; and active noise control aims to cancel the original sound field in the target area by generating a secondary sound field. In this paper, we briefly review the advances of the three different types of techniques with a discussion of their algorithms and applications.

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New Insights into Convergence Theory of Constrained Frequency-Domain Adaptive Filters

Cited by 3 publications

References 25 publications

Normalized Combinations of Proportionate Affine Projection Sign Subband Adaptive Filter

Normalized Combinations of Proportionate Affine Projection Sign Subband Adaptive Filter

A Frequency-Domain Output-Constrained Active Noise Control Algorithm Based on an Intuitive Circulant Convolutional Penalty Factor

A Review of Sound Field Control

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