Partitioning filters

Information Sciences

Volumn 17, Issue 3, 1979, Pages 177-193

  Lainiotis, Demetrios G ^a  

^a UNIVERSITY AT BUFFALO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

SIGNAL FILTERING AND PREDICTION;

EID: 0018456576     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/0020-0255(79)90016-1     Document Type: Article

References (29)

1. Estimation: a brief survey
2. A new approach to linear filtering and prediction problems
3. Optimal adaptive estimation: structure and parameter adaptation
4. Some new algorithms for recursive estimation in constant linear systems
5. A new algorithm for optimal filtering of discrete-time stationary processes
6. Partitioning: A unifying framework for adaptive systems, I: Estimation
7. Partitioning: A unifying framework for adaptive systems, II: Control
8. A unifying framework for linear estimation: Generalized partitioned algorithms
9. Partitioned estimation algorithms, I: Nonlinear estimation
10. Optimal nonlinear estimation
11. Partitioned estimation algorithms, II: Linear estimation
12. Partitioned linear estimation algorithms: discrete case
13. Optimal linear smoothing: continuous data case
14. Partitioned Riccati solutions and integration-free doubling algorithms
15. Generalized Chandrasekhar algorithms: time varying models
16. Discrete Riccati equation solutions: partitioned algorithms
17. Monte Carlo study of the optimal nonlinear state vector estimator for linear model and non-Gaussian initial state
18. Optimal state-vector estimation for non-Gaussian initial state-vector
19. A unifying approach to linear estimation via the partitioned algorithm I: Continuous models
20. A unifying approach to linear estimation via the partitioned algorithms, II: Discrete models
21. Partitioned Riccati algorithms
22. Generalized Chandrasekhar algorithms: time-varying models
23. Fast Riccati equation solution partitioned algorithms