Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/933902

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Title
Identification of state-space systems using a dual time-frequency domain approach
Author/Creator
Agüero, Juan C.;  Yuz, Juan I.;  Goodwin, Graham C.;  Tang, Wei
Institution
The University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science
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.
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
Date
2010
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Keyword(s)
frequency estimation;  matrix decomposition;  maximum likelihood estimation;  time frequency analysis;  discrete time systems
Resource Type
conference paper
Identifier
http://hdl.handle.net/1959.13/933902
Identifier
ISBN:9781424477463
Identifier
ISSN:0743-1546
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"Identification of state-space systems using a dual time-frequency domain approach"
 
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