Title
Exponential Myriad Smoothing Algorithm for Robust Signal Processing in \(\alpha \) -Stable Noise Environments.
Abstract
The sequential sample myriad has been proposed recently to estimate an unknown location parameter in real time by updating the current estimate when a new input sample is available. However, the algorithm is only capable of estimating an unknown constant (i.e., a time-invariant location parameter). In this paper, we propose a sequential myriad smoothing approach for tracking a time-varying location parameter corrupted by impulsive symmetric (alpha )-stable noise. By incorporating exponential weighting factor to the sequential algorithm, the new algorithm weighs the recent samples more heavily to provide effective tracking capability. Simulation results show that the proposed method outperforms the classical exponential smoothing and is as good as the running myriad smoother.
Year
DOI
Venue
2017
10.1007/s00034-017-0523-8
CSSP
Keywords
Field
DocType
$$\alpha $$α-Stable distribution, Impulsive noise, Sample myriad, Smoother
Exponential smoothing,Location parameter,Signal processing,Mathematical optimization,Weighting,Exponential function,Algorithm,Smoothing,Sequential algorithm,Mathematics
Journal
Volume
Issue
ISSN
36
11
1531-5878
Citations 
PageRank 
References 
1
0.38
8
Authors
3
Name
Order
Citations
PageRank
Benny Ming Kai Goh110.38
Heng-Siong Lim2459.65
Alan Wee-Chiat Tan393.59