DocumentCode :
434893
Title :
Minimax estimation of random elements: theory and applications
Author :
Siemenikhin, Konstantin V. ; Lebedev, Maxim V.
Author_Institution :
Probability Theor. Dept. of Appl. Math. & Phys. Fac., Moscow Aviation Inst., Russia
Volume :
4
fYear :
2004
fDate :
14-17 Dec. 2004
Firstpage :
3581
Abstract :
The problem of minimax estimation for the infinite-dimensional stochastic model is considered. The prior information about the random elements involved is formulated in term of second-order moment characteristics. The minimax estimation procedure is described and the corresponding numerical algorithm is presented. It is proved that the least favorable distribution of the model random elements is Gaussian. The efficiency of the proposed estimation algorithms is illustrated by means of the examples related to the signal and field robust processing.
Keywords :
estimation theory; minimax techniques; multidimensional systems; stochastic systems; Gaussian distribution; infinite-dimensional stochastic model; minimax estimation; numerical algorithm; random elements; second-order moment characteristics; signal processing; Algorithm design and analysis; Hilbert space; Minimax techniques; Random processes; Recursive estimation; Robustness; Signal processing; Stochastic processes; Sufficient conditions; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2004. CDC. 43rd IEEE Conference on
ISSN :
0191-2216
Print_ISBN :
0-7803-8682-5
Type :
conf
DOI :
10.1109/CDC.2004.1429268
Filename :
1429268
Link To Document :
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