Recursive least-squares algorithms with improved numerical stability and constrained least-squares algorithms for multichannel active noise control systems

Authors

  • M. Bouchard Sch. of Info. Technol./Engineering, University of Ottawa, Ottawa, Ont. K1N 6N5, Canada

Keywords:

Adaptive filtering, Algorithms, Computer simulation, Control systems, Convergence of numerical methods, Least squares approximations, Recursive functions, Multichannel active noise control (ANC) systems

Abstract

Recursive least squares (RLS) algorithms with improved numerical properties and constrained least-squares algorithms for multichannel active noise control (ANC) systems were discussed. The choice of the suitable algorithm for ANC, depends on the specific application. The inverse RLS algorithm has the best numerical properties, but it also has the highest computational load, while the least square lattice (LSL) algorithm has the lowest computational load, but requires the use of a forgetting factor with high value.

Additional Files

Published

2000-09-01

How to Cite

1.
Bouchard M. Recursive least-squares algorithms with improved numerical stability and constrained least-squares algorithms for multichannel active noise control systems. Canadian Acoustics [Internet]. 2000 Sep. 1 [cited 2024 Jun. 16];28(3):66-7. Available from: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/1293

Issue

Section

Proceedings of the Acoustics Week in Canada