Title :
A new Bayesian estimation approach for continuous-time systems
Author :
Hamidi-Hashemi, H.
Author_Institution :
Dept. of Electr. Eng., California State Univ., Fullerton, CA
Abstract :
In this paper, a new Bayesian estimation method is introduced. This new method provides estimation for the state variable through a locally correlated process. It utilizes both range and smoothing parameters. Therefore, it has the flexibility of the nonparametric approach as well as the adaptability of the Bayesian estimation. In addition, its convergence and some of its properties are discussed
Keywords :
Bayes methods; continuous time filters; continuous time systems; convergence; linear network analysis; state estimation; Bayesian estimation method; active filters; continuous-time systems; convergence; state variable estimation; Bandwidth; Bayesian methods; Convergence; Covariance matrix; Equations; Kernel; Polynomials; Smoothing methods; Spline; State estimation;
Conference_Titel :
Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
Conference_Location :
Lafayette, LA
Print_ISBN :
0-7803-2428-5
DOI :
10.1109/MWSCAS.1994.518977
