文章基本信息

标题：Recursive estimation of the scatter matrix of ECD: the Riemannian Information Gradient method ⁎ ⁎
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作者：Zhou Jialun ; Salem Said ; Yannick Berthoumieu 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：9
页码：713-718
DOI：10.1016/j.ifacol.2021.06.134
语种：English
出版社：Elsevier
摘要：AbstractECD (elliptically-contoured distribution) models have been found remarkably successful in representing natural signals. At present, the estimation of these models is at the heart of numerous signal processing applications. Unfortunately, state-of-the-art methods for estimating the parameters of an ECD, especially its scatter matrix, may turn out to have excessive computational complexity. To remedy this problem, the present work introduces the Riemannian information gradient method, for recursive (i.e. online) estimation of the scatter matrix. It is shown that this method holds a significant advantage in terms of computational complexity, while still achieving the same performance as state-of-the-art methods.
关键词：Keywordselliptically-contoured distributiononline estimationmaximum-likelihoodFisher information metric