Estimation of parameters of a harmonic chirp model
Abstract Here, we address the problem of estimation of the parameters of a harmonic chirp model, often encountered in speech and music applications. This model was introduced recently by Christensen and Jensen [1] as an extension of a standard harmonic model. We propose two methods of estimation: th...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-08-01
|
Series: | IET Signal Processing |
Online Access: | https://doi.org/10.1049/sil2.12038 |
id |
doaj-e8b48b5186f14b94bb0e9118409ac107 |
---|---|
record_format |
Article |
spelling |
doaj-e8b48b5186f14b94bb0e9118409ac1072021-08-02T08:20:02ZengWileyIET Signal Processing1751-96751751-96832021-08-0115637539510.1049/sil2.12038Estimation of parameters of a harmonic chirp modelRhythm Grover0Debasis Kundu1Amit Mitra2Theoretical Statistics and Mathematics Unit Indian Statistical Institute Delhi New Delhi IndiaDepartment of Mathematics and Statistics Indian Institute of Technology Kanpur Kanpur IndiaDepartment of Mathematics and Statistics Indian Institute of Technology Kanpur Kanpur IndiaAbstract Here, we address the problem of estimation of the parameters of a harmonic chirp model, often encountered in speech and music applications. This model was introduced recently by Christensen and Jensen [1] as an extension of a standard harmonic model. We propose two methods of estimation: the least squares estimation method and the approximate least squares estimation method. We establish the asymptotic properties of the least squares estimators as well as the approximate least squares estimators of the parameters of this model under the assumption of stationary errors. These asymptotic properties are proved analytically as well as corroborated through simulation experiments. We present two speech signal data sets and their analysis using both the estimation methods. The results show that the proposed methods perform reasonably well for estimating the unknown model parameters.https://doi.org/10.1049/sil2.12038 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rhythm Grover Debasis Kundu Amit Mitra |
spellingShingle |
Rhythm Grover Debasis Kundu Amit Mitra Estimation of parameters of a harmonic chirp model IET Signal Processing |
author_facet |
Rhythm Grover Debasis Kundu Amit Mitra |
author_sort |
Rhythm Grover |
title |
Estimation of parameters of a harmonic chirp model |
title_short |
Estimation of parameters of a harmonic chirp model |
title_full |
Estimation of parameters of a harmonic chirp model |
title_fullStr |
Estimation of parameters of a harmonic chirp model |
title_full_unstemmed |
Estimation of parameters of a harmonic chirp model |
title_sort |
estimation of parameters of a harmonic chirp model |
publisher |
Wiley |
series |
IET Signal Processing |
issn |
1751-9675 1751-9683 |
publishDate |
2021-08-01 |
description |
Abstract Here, we address the problem of estimation of the parameters of a harmonic chirp model, often encountered in speech and music applications. This model was introduced recently by Christensen and Jensen [1] as an extension of a standard harmonic model. We propose two methods of estimation: the least squares estimation method and the approximate least squares estimation method. We establish the asymptotic properties of the least squares estimators as well as the approximate least squares estimators of the parameters of this model under the assumption of stationary errors. These asymptotic properties are proved analytically as well as corroborated through simulation experiments. We present two speech signal data sets and their analysis using both the estimation methods. The results show that the proposed methods perform reasonably well for estimating the unknown model parameters. |
url |
https://doi.org/10.1049/sil2.12038 |
work_keys_str_mv |
AT rhythmgrover estimationofparametersofaharmonicchirpmodel AT debasiskundu estimationofparametersofaharmonicchirpmodel AT amitmitra estimationofparametersofaharmonicchirpmodel |
_version_ |
1721238545377525760 |