Title :
A FAST Algorithm for Adaptive Filtering
Author :
Arezki, Madjid ; Guessoum, Abderezak ; Meyrueis, Patrick
Author_Institution :
Dept. of Electron., Univ. of Saad Dahlab, Blida, Algeria
Abstract :
In this paper, we propose a new algorithm for adaptive filtering with fast convergence and low complexity. It is the result of a simplified fast transversal filter type algorithm, where the adaptation gain is obtained only from the forward prediction variables and using a new recursive method to compute the likelihood variable. This algorithm presents a certain interest, for the adaptation of very long filters, like those used in the problems of echo acoustic cancellation, due to its reduced complexity, its numerical stability and its convergence in the presence of the speech signal. Its computational complexity is of 6L, where L is the finite impulse response filter length and this is considerably reduced to 2L+4P when we use a reduced P-size (P¿L) forward predictor. Finally, some simulation results are presented and our algorithm shows an improvement in convergence over the normalized least mean square.
Keywords :
adaptive filters; computational complexity; least mean squares methods; recursive filters; speech processing; FAST algorithm; adaptive filtering; computational complexity; echo acoustic cancellation; fast transversal filter type algorithm; least mean square; likelihood variable; numerical stability; recursive method; speech signal; Adaptive algorithm; Adaptive filters; Computational complexity; Convergence; Filtering algorithms; Finite impulse response filter; Numerical stability; Resonance light scattering; Signal processing; Transversal filters;
Conference_Titel :
Systems, Signals and Image Processing, 2009. IWSSIP 2009. 16th International Conference on
Conference_Location :
Chalkida
Print_ISBN :
978-1-4244-4530-1
Electronic_ISBN :
978-1-4244-4530-1
DOI :
10.1109/IWSSIP.2009.5367738