A lower bound on the estimation error for Markov processes
- 1 December 1975
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Automatic Control
- Vol. 20 (6) , 785-788
- https://doi.org/10.1109/tac.1975.1101088
Abstract
A lower bound on the minimal mean-square error in estimating nonlinear Markov processes is presented. The bound holds for causal and uncausal filtering. The derivation is based on the Van Trees' version of the Cramér-Rao inequality.Keywords
This publication has 7 references indexed in Scilit:
- A lower bound on the estimation error for certain diffusion processesIEEE Transactions on Information Theory, 1976
- Filtering and control performance bounds with implications on asymptotic separationAutomatica, 1972
- Lower and upper bounds on the optimal filtering error of certain diffusion processesIEEE Transactions on Information Theory, 1972
- A general likelihood-ratio formula for random signals in Gaussian noiseIEEE Transactions on Information Theory, 1969
- Dynamical equations for optimal nonlinear filteringJournal of Differential Equations, 1967
- Conditional Markov ProcessesTheory of Probability and Its Applications, 1960
- On the Differentiability of Measures Corresponding to Random Processes. II. Markov ProcessesTheory of Probability and Its Applications, 1960