DocumentCode :
1609934
Title :
Recursive EM and SAGE algorithms
Author :
Chung, Pei Jung ; Böhme, Johann F.
Author_Institution :
Dept. of Electr. Eng. & Inf. Sci., Ruhr-Univ., Bochum, Germany
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
540
Lastpage :
543
Abstract :
This work is concerned with recursive procedures in which the data run through sequentially. Two stochastic approximation recursions derived from the EM (expectation-maximization).and SAGE (space-alternating generalized expectation-maximization). algorithms are proposed. We show that under regularity conditions, these recursions lead to strong consistency and asymptotic normality. Although the recursive EM and SAGE algorithm do not have the optimal convergence rate, they are usually easy to implement. As an example, we derive recursive procedures for direction of arrival (DOA) estimation. In numerical experiments both algorithms provide good results for low computational cost
Keywords :
approximation theory; convergence of numerical methods; direction-of-arrival estimation; iterative methods; recursive estimation; stochastic processes; DOA estimation; asymptotic normality; computational cost; consistency; convergence; direction of arrival estimation; recursive EM algorithms; recursive SAGE algorithms; regularity conditions; space-alternating generalized expectation-maximization algorithm; stochastic approximation recursions; Approximation algorithms; Computational efficiency; Convergence; Direction of arrival estimation; Information science; Iterative algorithms; Parameter estimation; Recursive estimation; Stability; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN :
0-7803-7011-2
Type :
conf
DOI :
10.1109/SSP.2001.955342
Filename :
955342
Link To Document :
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