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Analysis of the maximum likelihood, total least squares and principal component approaches for frequency response function estimation

Analysis of the maximum likelihood, total least squares and principal component approaches for frequency response function estimation
Analysis of the maximum likelihood, total least squares and principal component approaches for frequency response function estimation
This paper considers the problem of estimation frequency response functions (FRFs) for a single-input single-output (SISO) system in the presence of additive noise on both input and output measurements. It demonstrates that principle component analysis (PCA) can be employed to solve such problems and demonstrates that this is equivalent to the methods based on total least squares (TLS). FRF estimation is also cast as a problem in statistical inference and the use of the principle of maximum likelihood (ML) leads to a novel development of a generalised TLS scheme. This analysis also provides a framework within which one can compute asymptotic expressions for the variance of such estimators.
0022-460X
676-689
White, P.R.
2dd2477b-5aa9-42e2-9d19-0806d994eaba
Tan, M.H.
4d02e6ad-7915-491c-99cc-a1c85348267c
Hammond, J.K.
9ee35228-a62c-4113-8394-1b24df97b401
White, P.R.
2dd2477b-5aa9-42e2-9d19-0806d994eaba
Tan, M.H.
4d02e6ad-7915-491c-99cc-a1c85348267c
Hammond, J.K.
9ee35228-a62c-4113-8394-1b24df97b401

White, P.R., Tan, M.H. and Hammond, J.K. (2006) Analysis of the maximum likelihood, total least squares and principal component approaches for frequency response function estimation. Journal of Sound and Vibration, 290 (3-5), 676-689. (doi:10.1016/j.jsv.2005.04.029).

Record type: Article

Abstract

This paper considers the problem of estimation frequency response functions (FRFs) for a single-input single-output (SISO) system in the presence of additive noise on both input and output measurements. It demonstrates that principle component analysis (PCA) can be employed to solve such problems and demonstrates that this is equivalent to the methods based on total least squares (TLS). FRF estimation is also cast as a problem in statistical inference and the use of the principle of maximum likelihood (ML) leads to a novel development of a generalised TLS scheme. This analysis also provides a framework within which one can compute asymptotic expressions for the variance of such estimators.

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More information

Published date: 7 March 2006

Identifiers

Local EPrints ID: 28365
URI: https://eprints.soton.ac.uk/id/eprint/28365
ISSN: 0022-460X
PURE UUID: fc6981cf-658b-4386-96cd-57a2a1229035
ORCID for P.R. White: ORCID iD orcid.org/0000-0002-4787-8713

Catalogue record

Date deposited: 28 Apr 2006
Last modified: 06 Jun 2018 13:12

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