NDLI: Combination of Recursive Least <formula formulatype=inline> <tex Notation=TeX>$p$</tex></formula>-Norm Algorithms for Robust Adaptive Filtering in Alpha-Stable Noise

Content Provider	IEEE Xplore Digital Library
Author	Navia-Vazquez, A. Arenas-Garcia, J.
Copyright Year	1991
Abstract	A method for adaptively minimizing the lp norm relying on the convex combination of two recursive least p -norm (RLpN) filters is presented. The approach is of interest when the noise is not Gaussian, for instance in the presence of impulsive or alpha-stable (α-S) distributed noise. In these cases, the RLpN algorithm, aiming at recursively minimizing the lp norm, offers a more stable and robust solution than adaptive filtering schemes based on the minimization of the squared error. However, since the RLpN solution cannot be obtained in closed form for p ≠ 2, it is necessary to introduce some approximations that critically affect the filter behavior. The main observed drawback is a poor convergence rate in nonstationary scenarios, especially in the presence of abrupt changes in the model. In this correspondence, we show how this problem can be overcome by relying on convex combinations of two RLpN filters with long and short memories. The proposed methods are empirically shown to outperform state-of-the-art methods for this problem, requiring just slightly higher computation than its close competitors.
Sponsorship	IEEE Signal Processing Society
Starting Page	1478
Ending Page	1482
Page Count	5
File Size	413593
File Format	PDF
ISSN	1053587X
Volume Number	60
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing algorithms Noise Approximation algorithms Robustness Convergence Least squares approximation system identification Alpha-stable noise combination filters $l_{p}$ norm cost functions
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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