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General Robust Proportionate NSAF Algorithm With a Step-Size Converter
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DOI：10.1109/TCSII.2022.3216027.png)
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摘要
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To identify sparse systems in the presence of impulsive noises, we propose a general robust proportionate normalized subband adaptive filtering (R-PNSAF) algorithm. Furthermore, to achieve fast convergence and low steady-state misadjustment, we develop a step-size converter (SSC) for R-PNSAF which results in the SSC-R-PNSAF algorithm, which selects the optimal step-size by comparing the mean square deviation at each iteration of the algorithm under given different step-sizes. Simulation results demonstrate the superiority of the proposed scheme in the a-stable noise scenario over the competing techniques.
Keyword:
Convergence
Steady-state
Approximation algorithms
Sparse matrices
Computational complexity
Additive noise
Acoustics
Impulsive noise
proportionate algorithm
subband adaptive filter
step-size converter
期刊
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4.9
论文数:
8.8K
被引数:
2.5W
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SIGNAL PROCESSINGIF3.6
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