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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Djendi, M. Guessoum, A. Benallal, A. Bouchard, M. Berkani, D. |
| Copyright Year | 2004 |
| Description | Author affiliation: Laboratory of Signal Process. & Imaging, BLIDA Saad Dahleb Univ., Algeria (Djendi, M.; Guessoum, A.; Benallal, A.) |
| Abstract | In this paper, five new versions of the fast Newton transversal filter algorithm FNTF are presented. The first algorithm is based on a simple modification of the filtering part, by introducing a scalar accelerator parameter. The second algorithm is based on the use of block filtering technique to improve the local filter coefficients. The third one is a modification of the second by the use of the final filtering errors to update the filters coefficients. The fourth and the fifth ones are based, respectively, on the combination of features from the first, the second and the third version. We present, also, a new structure of the prediction part of each new algorithms. These five new algorithms were proposed to improve the tracking ability of time varying systems (acoustic systems). The different algorithms and their comparative results are presented. |
| Sponsorship | IEEE IEEE Finland Section IEEE SP/CAS Chapter, Finland EURASIP UCSB Tampere Univ. of Technol. Ecole Superieure des Sciences et Techniques de Tunis, ESSTT, Univ. of Manouba |
| Starting Page | 701 |
| Ending Page | 704 |
| File Size | 405800 |
| Page Count | 4 |
| File Format | |
| ISBN | 0780383796 |
| DOI | 10.1109/ISCCSP.2004.1296508 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-03-21 |
| Publisher Place | Tunisia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Echo cancellers Adaptive filters Signal processing algorithms Filtering algorithms Transversal filters Speech Electronic mail Error correction System identification Convergence |
| Content Type | Text |
| Resource Type | Article |
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