ConferencePaper
Proceedings of the IEEE Conference on Decision and Control  (2010)

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

Aguero, J.C.; Goodwin G.C.; Yuz J.I.; Tang, W

Keywords: systems, domains, models, state, space, variables, domain, time, errors, frequency, data, transformations, maximum, estimation, likelihood, time-domain, analysis, expectation, metadata, in, Linear, dual, estimate, Discrete-time, maximization, state-space, Frequency-domain

Abstract

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. ©2010 IEEE.

Más información

Título de la Revista: Proceedings of the IEEE Conference on Decision and Control
Editorial: IEEE
Fecha de publicación: 2010
Página de inicio: 2863
Página final: 2868
URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-79953148931&partnerID=q2rCbXpz