Notes on M-estimation in exponential signal models
type: Item
instance of: scholarly article
title: Notes on M-estimation in exponential signal models
zbMATH Open document ID: 1473.62084
author: Shu Ding
author: Kwok-Wai Tam
author: Yuehua Wu
published in: Communications in Mathematics and Statistics
publication date: 2021-08-19T00:00:00Z
review text: Consider the undamped exponential signal model \[ y_n=\sum_{j=1}^p\alpha_je^{\sqrt{-1}\omega_jn}+w_n\,, \] for \(n=1,\ldots,N\), where the \(y_n\) are observed data, the \(\omega_j\) are unknown frequencies, the \(\alpha_j\) are unknown amplitudes and the \(w_n\) are noise terms. The present paper focuses on maximum likelihood-type estimators of the \(\omega_j\), in particular proving asymptotic normality for such estimators under some mild assumptions. The authors also provide a recursive algorithm for the computation of these estimators which gives consistent estimates under mild conditions, and investigate their results using a numerical study.
reviewed by: Fraser Daly
Mathematics Subject Classification ID: 62F12
Mathematics Subject Classification ID: 62E20
Mathematics Subject Classification ID: 60F05
Mathematics Subject Classification ID: 94A12
zbMATH DE Number: 7383346
zbMATH Keywords: exponential signal model
zbMATH Keywords: M-estimation
zbMATH Keywords: limiting distribution
zbMATH Keywords: recursive algorithm
zbMATH Keywords: consistency
Wikidata QID: Q115600727
MaRDI profile type: Publication
full work available at URL: s40304-019-00190-7
OpenAlex ID: W2972567927
cites work: Q4310811
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cites work: Q3723487
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DOI: 10.1007/S40304-019-00190-7
description: scientific article; zbMATH DE number 7383346