A non‐uniform NSAF‐SF adaptive algorithm
Abstract Speech enhancement and acoustic noise reduction are two important tasks where adaptive filtering algorithms emerge as a competitive solution. Unfortunately, in such applications the convergence rate of the system identification is hampered when the excitation data is highly correlated. Subb...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Wiley
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/7a9dfa24b1014b2580664cc21309dd50 |
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| Sumario: | Abstract Speech enhancement and acoustic noise reduction are two important tasks where adaptive filtering algorithms emerge as a competitive solution. Unfortunately, in such applications the convergence rate of the system identification is hampered when the excitation data is highly correlated. Subband adaptive algorithms have been developed to address such issue. A recently proposed low‐complexity subband adaptive structure with sparse subfilters is generalised, in order to permit a non‐uniform filter bank structure. This generalisation brings additional flexibility to the resulting critically decimated adaptive structure, which allows one to adapt it to the idiosyncrasies of the application of interest without losing the perfect‐reconstruction property. A closed‐form solution for the optimal values that the adaptive coefficient should assume in order to accurately emulate a given impulse response is derived. Simulations reveal that the resulting algorithm may outperform recently published subband adaptive filtering algorithms, thereby requiring even less computational effort. |
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