On Frequency Estimation for Partially Observed System with Small Noises in State and Observation Equations

• Published in: Komunikácie : vedecké listy Žilinskej univerzity = Communications : scientific letters of the University of Žilina Vol. 20; no. 1; pp. 67 - 72
• Main Authors: Chernoyarov, Oleg V, Kutoyants, Yury A, Marcokova, Mariana
• Format: Journal Article
• Language: English
• Published: University of Žilina 2018; Žilinská univerzita v Žilině
• Subjects: bayesian approach; characteristics of estimators; Energy and Environmental Studies; frequency estimator; ICT Information and Communications Technologies; maximum likelihood method; Methodology and research technology; partially observed linear system; small noise asymptotic; stochastic signal; stochastic signal; Bayesian approach; small noise asymptotic; maximum likelihood method; frequency estimator; characteristics of estimators; partially observed linear system
• ISSN: 1335-4205; 2585-7878
• DOI: 10.26552/com.C.2018.1.67-72

We consider the problem of frequency estimation of the periodic signal multiplied by a Gaussian process (Ornstein-Uhlenbeck) and observed in the presence of the white Gaussian noise. We demonstrate the consistency and asymptotic normality of the maximum likelihood and Bayesian estimators in the sense of the small noise asymptotics. The model of observations is a linear nonhomogeneous partially observed system and the construction of the estimators is based on the Kalman-Bucy filtration equations. For the study of the properties of the estimators, we apply the techniques introduced by Ibragimov and Has’minskii.