Citation

Goh, Benny Ming Kai and Lim, Heng Siong and Tan, Alan Wee Chiat (2017) Exponential Myriad Smoothing Algorithm for Robust Signal Processing in α-Stable Noise Environments. Circuits, Systems, and Signal Processing, 36 (11). pp. 4468-4481. ISSN 0278081X

Text 10.1007%2Fs00034-017-0523-8.pdf Restricted to Repository staff only Download (789kB)

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 αα -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.

Item Type:	Article
Uncontrolled Keywords:	α-Stable distribution, Impulsive noise, Sample myriad, Smoother, Signal Processing
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	29 Jul 2020 06:28
Last Modified:	29 Jul 2020 06:28
URII:	http://shdl.mmu.edu.my/id/eprint/7002

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