Title :
Recursive algorithms for Bayes smoothing with uncertain observations
Author :
Askar, Murat ; Derin, Haluk
Author_Institution :
Middle East Technical University, Ankara, Turkey
fDate :
5/1/1984 12:00:00 AM
Abstract :
Recursive algorithms for the Bayes solution of fixed-interval, fixed-point, and fixed-lag smoothing under uncertain observations are presented. The Bayes smoothing algorithms are obtained for a Markovian system model with Markov uncertainty, a model more general than the one used in linear smoothing algorithms. The Bayes fixed-interval smoothing algorithm is applied to a Gauss-Markov example. The simulation results for this example indicate that the MSE performance of the Bayes smoother is significantly better than that of the linear smoother.
Keywords :
Bayes procedures; Gaussian processes; Markov processes; Recursive estimation; Smoothing methods; Uncertain systems; Additive noise; Application software; Filtering algorithms; Gaussian noise; Gaussian processes; Recursive estimation; Smoothing methods; Uncertainty;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1984.1103554