A Fast Robust Recursive Least-Squares Algorithm

We present a fast robust recursive least-squares (FRRLS) algorithm based on a recently introduced new framework for designing robust adaptive filters. The algorithm is the result of minimizing a cost function subject to a time-dependent constraint on the norm of the filter update. Although the chara...

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 57; no. 3; pp. 1209 - 1216
Main Authors: Vega, L.R., Rey, H., Benesty, J., Tressens, S.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.03.2009
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Acoustic applications
Acoustic echo cancellation
Acoustic testing
Adaptive filters
Algorithm design and analysis
Algorithms
Applied sciences
Approximation
Asymptotic properties
Closed-form solution
Cost function
Detection, estimation, filtering, equalization, prediction
Echo cancellers
Exact sciences and technology
Exact solutions
impulsive noise
Information, signal and communications theory
Least squares method
Mathematical analysis
Miscellaneous
Recursive
recursive least-squares algorithm
robust filtering
Robustness
Signal and communications theory
Signal processing
Signal, noise
System identification
System testing
Telecommunications and information theory
Acoustic echo cancellation
Noise reduction
Asymptotic behavior
Theoretical study
Updating
Adaptive filter
Acoustic signal processing
Echo suppression
Recursive algorithm
Temporal constraint
Exact solution
robust filtering
Robust control
Time dependence
Pulse noise
Acoustic noise
Least squares method
Recursive method
Signal processing
Cost function
impulsive noise
System identification
Approximate solution
recursive least-squares algorithm
ISSN:1053-587X, 1941-0476
Online Access:Get full text
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Description
Summary:We present a fast robust recursive least-squares (FRRLS) algorithm based on a recently introduced new framework for designing robust adaptive filters. The algorithm is the result of minimizing a cost function subject to a time-dependent constraint on the norm of the filter update. Although the characteristics of the exact solution to this problem are known, there is no closed-form solution in general. However, the approximate solution we propose is very close to the optimal one. We also present some theoretical results regarding the asymptotic behavior of the algorithm. The FRRLS is then tested in different environments for system identification and acoustic echo cancellation applications.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2008.2010643