Identification of state-space systems using a dual time-frequency domain approach

Title: Identification of state-space systems using a dual time-frequency domain approach
Creator: Agüero, Juan C.; Yuz, Juan I.; Goodwin, Graham C.; Tang, Wei
Relation: 49th IEEE Conference on Decision and Control (CDC 2010). Proceedings of the 49th IEEE Conference on Decision and Control (Atlanta, GA 15-17 December, 2010) p. 2863-2868
Publisher Link: http://dx.doi.org/10.1109/CDC.2010.5717056
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Resource Type: conference paper
Date: 2010
Description: In this paper we obtain the maximum likelihood estimate of the parameters of discrete-time state-space models by using a dual time-frequency domain approach. We propose an Expectation Maximization formulation that considers a (non-bijective) linear transformation of the available data. Such a transformation may correspond to different options: selection of time-domain data, transformation to the frequency domain, or selection of frequency-domain data obtained from time-domain samples. We also explore the application of these ideas to Errors-In-Variables systems.
Subject: frequency estimation; matrix decomposition; maximum likelihood estimation; time frequency analysis; discrete time systems
Identifier: http://hdl.handle.net/1959.13/933902
Identifier: uon:11745
Identifier: ISBN:9781424477463
Identifier: ISSN:0743-1546
Language: eng
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