Frequency domain maximum likelihood estimation of linear dynamic errors-in-variables models

- This paper studies the linear dynamic errors-in-variables problem in the frequency domain. First the identifiability is shown under relaxed conditions. Next a frequency domain Gaussian maximum likelihood (ML) estimator is constructed that can handle discrete-time as well as continuous-time models on (a) part(s) of the unit circle or imaginary axis. The ML estimates are calculated via a computational simple and numerical stable Newton-Gauss minimization scheme. Finally the Cramér-Rao lower bound is derived. VERSION January 18, 2006

• Type: Journal
• Year: 2007
• Where: AUTOMATICA
• Authors: Rik Pintelon, Johan Schoukens
• Keywords: AUTOMATICA 2007, Domain Gaussian Maximum, Frequency Domain, Linear Dynamic Errors-in-variables