Robust processing of heavy tails signals - comparison of approaches

Liam Galin*, Hagit Messer

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper deals with robust estimation of AR parameters. We compare the performance of the LMS algorithm to the performance of two robust, adaptive algorithms: the LMAD algorithm of Shao and Nikias in which the error signal in the LMS algorithm is hard-limited before used to control the weights, and the LLMS algorithm in which the input process is soft-limited before the LMS algorithm is applied. The comparison is done in terms of rate of convergence and stability (steady state variance). We show that with a proper choice of limiting level, the LLMS algorithm outperforms the LMAD algorithms when applied to symmetric, α stable processes of 1 ≤ α ≤ 2.

Original languageEnglish
Pages230-233
Number of pages4
StatePublished - 1996
EventProceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96 - Corfu, Greece
Duration: 24 Jun 199626 Jun 1996

Conference

ConferenceProceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96
CityCorfu, Greece
Period24/06/9626/06/96

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