Robust least mean mixed norm adaptive filtering for α-stable random processes

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Robust least mean mixed norm adaptive filtering for α-stable random processes.pdf (303.95 KB)

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1997

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Abstract

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.

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Proceedings of the 1997 IEEE International Symposium on Circuits and Systems

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IEEE

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Keywords

Adaptive algorithms, Mathematical models, Probability, Random processes, Spurious signal noise, Robust least mean mixed norm adaptive algorithm, Robust least mean mixed norm adaptive filtering, Adaptive filtering

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http://hdl.handle.net/11693/27713

Published Version (Please cite this version)

https://www.doi.org/10.1109/ISCAS.1997.612781

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Scholarly Publications - Electrical and Electronics Engineering

Language

English

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Conference Paper