Title :
Filtering and modeling using covariance information in linear continuous systems
Author :
Nakamori, Seiichi
Author_Institution :
Dept. of Technol., Kagoshima Univ., Japan
Abstract :
Filtering and modeling procedures using covariance information are proposed. The sequential algorithms for the filtering estimate of x (t) from the Wiener-Hopf integral equation are presented based on innovations theory. A numerical simulation result shows that the present algorithms are quite feasible in linear continuous stochastic systems
Keywords :
filtering and prediction theory; integral equations; linear systems; modelling; stochastic systems; Wiener-Hopf integral equation; covariance information; filtering estimate; innovations theory; linear continuous stochastic systems; modeling; sequential algorithms; Continuous time systems; Equations; Gaussian noise; Information filtering; Information filters; Kernel; Nonlinear filters; State estimation; Technological innovation; White noise;
Conference_Titel :
Systems Engineering, 1992., IEEE International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-7803-0734-8
DOI :
10.1109/ICSYSE.1992.236890
