Asymptotic Parameter Estimation for a Class of Linear Stochastic Systems Using Kalman-Bucy Filtering. (1st September 2012)

• Record Type: Journal Article
• Authors: Kan, Xiu; Shu, Huisheng; Che, Yan
• Other Names: Hu Jun Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2012(2012)
• Publication Date: 2012-09-01
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2012/342705
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The asymptotic parameter estimation is investigated for a class of linear stochastic systems with unknown parameter θ : d X t = ( θ α ( t ) + β ( t ) X t ) d t + σ ( t ) d W t . Continuous-time Kalman-Bucy linear filtering theory is first used to estimate the unknown parameter θ based on Bayesian analysis. Then, some sufficient conditions on coefficients are given to analyze the asymptotic convergence of the estimator. Finally, the strong consistent property of the estimator is discussed by comparison theorem.