Nonparametric spectral analysis with missing data via the em algorithm

被引：0

作者：

Li, J ^{[1
]}

Wang, YW ^{[1
]}

Stoica, P ^{[1
]}

Marzetta, TL ^{[1
]}

机构：

[1] Univ Florida, Dept ECE, Gainesville, FL 32611 USA

来源：

CONFERENCE RECORD OF THE THIRTY-EIGHTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2 | 2004年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We consider nonparametric complex spectral estimation of data sequences with missing samples occurring in arbitrary patterns. Several nonparametric algorithms have recently been developed to deal with the missing-data problem. They include, for example, GAPES for gapped data and PG-APES, PG-CAPON for periodically gapped data. However, they are not really suitable for the general missing-data problem where the missing data samples occur in arbitrary patterns. In this paper, we deal with a general missing-data spectral estimation problem for which we develop two nonparametric missing-data amplitude and phase estimation (MAPES) algorithms, both of which make use of the expectation maximization (EM) algorithm. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.

引用

页码：8 / 12

页数：5

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