A practical variable forgetting factor recursive least-squares algorithm
In the context of adaptive filtering, the recursive least-squares (RLS) is a very popular algorithm, especially for its fast convergence rate. The most important parameter of this algorithm is the forgetting factor. It is well-known that a constant value of this parameter leads to a compromise betwe...
Uloženo v:
| Vydáno v: | 2014 11th International Symposium on Electronics and Telecommunications (ISETC) s. 1 - 4 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.11.2014
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| Témata: | |
| ISBN: | 9781479972661, 1479972665 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | In the context of adaptive filtering, the recursive least-squares (RLS) is a very popular algorithm, especially for its fast convergence rate. The most important parameter of this algorithm is the forgetting factor. It is well-known that a constant value of this parameter leads to a compromise between misadjustment and tracking. In this paper, we present a variable forgetting factor approach, aiming to better compromise between the performance criteria of the RLS algorithm. Also, we propose a practical solution to estimate the power of the system noise (in a system identification scenario), which is required within the algorithm. Experiments performed in the context of network echo cancellation support the advantages of the proposed approach. |
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| ISBN: | 9781479972661 1479972665 |
| DOI: | 10.1109/ISETC.2014.7010812 |

