A Family of Variable Step-Size Normalized Subband Adaptive Filter Algorithms Using Statistics of System Impulse Response
This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison wit...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Iran University of Science and Technology
2013-03-01
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| Series: | Iranian Journal of Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://ijeee.iust.ac.ir/browse.php?a_code=A-10-68-4&slc_lang=en&sid=1 |
| Summary: | This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse
response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison with NSAF, the VSS-NSAF algorithm has faster convergence speed and lower MSD. To reduce the computational complexity of VSSNSAF, the VSS selective partial update NSAF (VSS-SPU-NSAF) is proposed where the filter coefficients are partially updated in each subband at every iteration. We demonstrated the good performance of the proposed algorithms in convergence speed and steady-state MSD for a system identification set-up. |
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| ISSN: | 1735-2827 2383-3890 |