Numerical differentiation and parameter estimation in higher-order linear stochastic systems

1996 ◽  
Vol 41 (4) ◽  
pp. 522-532 ◽  
Author(s):  
T.E. Duncan ◽  
P. Mandl ◽  
B. Pasik-Duncan
Keyword(s):  
Parameter Estimation ◽  
Stochastic Systems ◽  
Numerical Differentiation ◽  
Higher Order ◽  
Order Linear ◽  
Linear Stochastic Systems

scholarly journals Asymptotic Parameter Estimation for a Class of Linear Stochastic Systems Using Kalman-Bucy Filtering

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Xiu Kan ◽  
Huisheng Shu ◽  
Yan Che
Keyword(s):  
Parameter Estimation ◽  
Continuous Time ◽  
Unknown Parameter ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Asymptotic Convergence ◽  
Linear Filtering ◽  
Linear Stochastic Systems ◽  
Asymptotic Parameter ◽  
Consistent Property

The asymptotic parameter estimation is investigated for a class of linear stochastic systems with unknown parameterθ:dXt=(θα(t)+β(t)Xt)dt+σ(t)dWt. Continuous-time Kalman-Bucy linear filtering theory is first used to estimate the unknown parameterθbased 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.

scholarly journals A note on sampling and parameter estimation in linear stochastic systems

1999 ◽  
Vol 44 (11) ◽  
pp. 2120-2125 ◽  
Author(s):  
T.E. Duncan ◽  
P. Mandl ◽  
B. Pasik-Duncan
Keyword(s):  
Parameter Estimation ◽  
Stochastic Systems ◽  
Linear Stochastic Systems
Sign in / Sign up

Export Citation Format

Share Document