The FLS-QR algorithm for adaptive filtering: The case of multichannel signals
MG Bellanger, PA Regalia - Signal Processing, 1991 - Elsevier
MG Bellanger, PA Regalia
Signal Processing, 1991•ElsevierAbstract The Fast Least Squares (FLS) algorithms based on the QR triangular
decomposition of the input signal matrix and developed for the case of one-dimensional (1-
D) signals can be extended to handle the case of multi-dimensional (MD) or multichannel
signals. A particularly simple, flexible and robust approach for K-dimensional signals
consists of running the 1-D algorithm K times.
decomposition of the input signal matrix and developed for the case of one-dimensional (1-
D) signals can be extended to handle the case of multi-dimensional (MD) or multichannel
signals. A particularly simple, flexible and robust approach for K-dimensional signals
consists of running the 1-D algorithm K times.
Abstract
The Fast Least Squares (FLS) algorithms based on the QR triangular decomposition of the input signal matrix and developed for the case of one-dimensional (1-D) signals can be extended to handle the case of multi-dimensional (MD) or multichannel signals. A particularly simple, flexible and robust approach for K-dimensional signals consists of running the 1-D algorithm K times.
Elsevier
Showing the best result for this search. See all results