Discrete-time estimation of a Markov chain with marked point process observations. Application to markovian jump filtering

IEEE Transactions on Automatic Control

Volumn 46, Issue 6, 2001, Pages 903-908

  Allam, S ^a   Dufour, F ^a   Bertrand, P ^a  

^a CNRS   (France)

Author keywords

Estimation; Filtering; Marked point processes; Markov chain; Markovian jump systems

Indexed keywords

EXPECTATION MINIMIZATION (EM) PROCEDURES; MARKED POINT PROCESS (MPP); MARKOVIAN JUMP FILTERING;

ALGORITHMS; COMPUTER SIMULATION; GAUSSIAN NOISE (ELECTRONIC); MARKOV PROCESSES; MATHEMATICAL MODELS; MONTE CARLO METHODS; PROBABILITY; SET THEORY; STATE ESTIMATION; STATE SPACE METHODS; WHITE NOISE;

DISCRETE TIME CONTROL SYSTEMS;

EID: 0035365617     PISSN: 00189286     EISSN: None     Source Type: Journal    
DOI: 10.1109/9.928593     Document Type: Article

References (10)

1. Survival models and martingale dynamics
2. The filtered counting process and its applications to stochastic manufacturing systems
3. Filtering the histories of a partially observed marked point process
4. On the unnormalized solution of the filtering problem with counting process observations
5. Discrete time nonlinear filtering with marked point process observations
6. Maximum likelihood from incomplete data via the EM algorithm
7. Kalman filtering for linear systems with coefficients driven by a hidden Markov jump process
8. Exact hybrid filter in discrete time