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Robust Adaptation in Impulsive Noise.
- Source :
- IEEE Transactions on Signal Processing; Jun2016, Vol. 64 Issue 11, p2851-2865, 15p
- Publication Year :
- 2016
-
Abstract
- The popular least-mean-squares (LMS) algorithm for adaptive filtering is nonrobust against impulsive noise in the measurements. The presence of this type of noise degrades the transient and steady-state performance of the algorithm. Since the distribution of the impulsive noise is generally unknown, a robust semi-parametric approach to adaptive filtering is warranted, where the output error nonlinearity is adapted jointly with the parameter of interest. In this paper, a robust adaptive filtering algorithm is developed that effectively learns and tracks the output error distribution to improve estimation performance. The performance of the algorithm is analyzed mathematically and validated experimentally. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1053587X
- Volume :
- 64
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 114706274
- Full Text :
- https://doi.org/10.1109/TSP.2016.2535239