Title
Dually Regularized Recursive Prediction Error identification for acoustic feedback and echo cancellation
Abstract
Recursive prediction error (RPE) identification algorithms are attractive alternatives to the traditional least-squares-based adaptive filtering algorithms for, e.g., room impulse response identification, in such applications as acoustic feedback and echo cancellation. It has however been observed that a recently proposed RPE algorithm suffers from numerical problems due to a scaling ambiguity in the calculation of the auxiliary variables. This problem is tackled by regularizing the identification of some of the auxiliary variables, which is called “dual regularization”. This leads to a class of Dually Regularized Recursive Prediction Error (DR-RPE) identification algorithms, with different choices of regularization methods (Tikhonov or Levenberg-Marquardt) and matrices (possibly incorporating prior knowledge). Simulation results confirm that the DR-RPE algorithms do not exhibit numerical problems, and as a consequence produce more accurate estimates of the room impulse response and of the auxiliary variables.
Year
Venue
Field
2007
European Signal Processing Conference
Tikhonov regularization,Signal processing,Impulse response,Computer science,Algorithm,Linear prediction,Speech recognition,Regularization (mathematics),Adaptive filter,System identification,Numerical linear algebra
DocType
ISBN
Citations 
Conference
978-839-2134-04-6
2
PageRank 
References 
Authors
0.46
3
3
Name
Order
Citations
PageRank
Toon van Waterschoot115714.29
Geert Rombouts216714.46
Marc Moonen33673326.91