Charm-based estimator for non-Gaussian moving-average process

Alon Slapak, Arie Yeredor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Blind Moving-Average (MA) parameters estimation methods often resort to higher-order-statistics (HOS) in the form of high-order moments or cumulants in order to retrieve the phase of the generating system when no phase information, e.g., minimum-phase, is available. In this work, a new generic statistic is proposed - called the characteristic mean or charm in short - a generalization of the ordinary mean vector, which nonetheless carries a special form of HOS. The charm is parameterized by a parameters-vector called processing-point, which, when properly selected, conveniently controls the trade-off between the charm's HOS information content and the variance of its sample-estimate. A blind charm-based iterative algorithm is proposed, involving data-driven selection of the processing-point. The resulting algorithm - called CHARMA - is shown to significantly outperform ordinary HOS-based algorithms.

Original languageEnglish
Title of host publication2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
DOIs
StatePublished - 2012
Event2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012 - Eilat, Israel
Duration: 14 Nov 201217 Nov 2012

Publication series

Name2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012

Conference

Conference2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
Country/TerritoryIsrael
CityEilat
Period14/11/1217/11/12

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