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.
Agüero, J. C., Yuz, J. I., Goodwin, G. C., & Tang, W. (2010). Proceedings of the IEEE Conference on Decision and Control. 2863-2868. Papel presentado en conference, . https://doi.org/10.1109/CDC.2010.5717056