Title :
Recursive least-squares algorithms with good numerical stability for multichannel active noise control
Author :
Yu, F. ; Bouchard, M.
Author_Institution :
Sch. of Inf. Technol. & Eng., Ottawa Univ., Ont., Canada
Abstract :
Some recursive least-squares algorithms for multichannel active noise control have recently been introduced, including computationally efficient (i.e. "fast") versions. However, these previously published algorithms suffer from numerical instability due to finite precision computations. Numerically robust recursive least-squares algorithms for multichannel active noise control systems are introduced, using QR decompositions and lattice structures. It is shown through simulations of broadband multichannel active noise control that the recursive least-squares algorithms introduced are indeed more numerically robust than the previously published algorithms, while keeping the same convergence behavior, and therefore they are more suitable for practical implementations
Keywords :
active noise control; adaptive filters; least squares approximations; matrix decomposition; numerical stability; recursive estimation; QR decompositions; adaptive filters; broadband multichannel ANC; convergence; lattice structures; multichannel active noise control; numerical instability; numerical robustness; numerical stability; recursive least-squares algorithms; Acoustic sensors; Active noise reduction; Actuators; Adaptive filters; Delay; Finite impulse response filter; Noise robustness; Numerical stability; Sensor phenomena and characterization; Sensor systems;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
Print_ISBN :
0-7803-7041-4
DOI :
10.1109/ICASSP.2001.940344