Accelerating the convergence of the filtered-x lms algorithm through transform-domain optimisation
| Autor: | Alain Berry, Chon Tam Le Donh, B. Paillard, J. Nicolas |
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| Rok vydání: | 1995 |
| Předmět: |
Recursive least squares filter
Computational complexity theory Mechanical Engineering Aerospace Engineering Computer Science Applications Least mean squares filter Active noise control system Control and Systems Engineering Control theory Kalman algorithm Lattice (order) Test platform Signal Processing Civil and Structural Engineering Mathematics |
| Zdroj: | Mechanical Systems and Signal Processing. 9:445-464 |
| ISSN: | 0888-3270 |
| DOI: | 10.1006/mssp.1995.0035 |
| Popis: | This paper presents an investigation into the use of a transform-domain optimisation, to accelerate the convergence of the filtered-x least mean squares (LMS) algorithm. It is illustrated by results from a real-time active noise control system, cancelling the noise propagating in a one-dimensional duct. On this real-time test platform, we compare the convergence behaviour of the transform-domain filtered-x LMS, to the convergence behaviour of the standard filtered-x LMS. It is shown that the near optimal convergence speed of the transform-domain filtered-x LMS algorithm, its structural simplicity, and its low computational complexity make it a good alternative to other fast algorithms such as the recursive least squares algorithm, the fast Kalman algorithm, or other approaches based on lattice filters. |
| Databáze: | OpenAIRE |
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