DocumentCode :
1347497
Title :
Array algorithms for H estimation
Author :
Hassibi, Babak ; Kailath, Thomas ; Sayed, Ali H.
Author_Institution :
Inf. Syst. Lab., Stanford Univ., CA, USA
Volume :
45
Issue :
4
fYear :
2000
fDate :
4/1/2000 12:00:00 AM
Firstpage :
702
Lastpage :
706
Abstract :
We develop array algorithms for H filtering. These algorithms can be regarded as the Krein space generalizations of H 2 array algorithms, which are currently the preferred method fur implementing H2 filters. The array algorithms considered include two main families: square-root array algorithms, which are typically numerically more stable than conventional ones, and fast array algorithms which, when the system is time-invariant, typically offer an order of magnitude reduction in the computational effort. Both have the interesting feature that one does not need to explicitly check for the positivity conditions required for the existence of H filters, as these conditions are built into the algorithms themselves. However, since H square-root algorithms predominantly use J-unitary transformations, rather than the unitary transformations required in the H2 case, further investigation is needed to determine the numerical behavior of such algorithms
Keywords :
estimation theory; filtering theory; H estimation; H filtering; H square-root algorithms; H2 array algorithms; J-unitary transformations; Krein space generalizations; fast array algorithms; positivity conditions; square-root array algorithms; Filtering; Hilbert space; Information systems; Kalman filters; Random variables; Recursive estimation; Riccati equations; Robustness; State estimation; Uncertainty;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/9.847105
Filename :
847105
Link To Document :
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