Robust least mean mixed norm adaptive filtering for α-stable random processes
Date
1997Source Title
Proceedings of the 1997 IEEE International Symposium on Circuits and Systems
Print ISSN
0271-4310
Publisher
IEEE
Pages
2296 - 2299
Language
English
Type
Conference PaperItem Usage Stats
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Metadata
Show full item recordAbstract
Based on the concept of Fractional Lower Order Statistics (FLOS), we present the Robust Least Mean Mixed Norm (RLMMN) adaptive algorithm for applications in impulsive environments modeled by α-stable distributions. A sufficient condition for finite variance of the update term is obtained for the underlying α-stable process. Simulation results are provided regarding the identification of the parameters of an AR system.
Keywords
Adaptive algorithmsMathematical models
Probability
Random processes
Spurious signal noise
Robust least mean mixed norm adaptive algorithm
Robust least mean mixed norm adaptive filtering
Adaptive filtering
Permalink
http://hdl.handle.net/11693/27713Published Version (Please cite this version)
https://www.doi.org/10.1109/ISCAS.1997.612781Collections
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