Title :
Fast adaptive eigenvalue decomposition: a maximum likelihood approach
Author :
Riou, Christian ; Chonavel, Thierry
Author_Institution :
SC Dept., ENSTB, Brest, France
Abstract :
A new adaptive subspace estimation algorithm is presented, based on the maximisation of the likelihood functional. It requires little computational cost and the particular structure of the algorithm ensures the orthonormality of the estimated basis of eigenvectors. Application to moving sources localization shows the very good behavior of the algorithm when applied to problems of practical interest
Keywords :
adaptive estimation; adaptive signal processing; convergence of numerical methods; covariance matrices; eigenvalues and eigenfunctions; matrix decomposition; maximum likelihood estimation; adaptive eigenvalue decomposition; adaptive subspace estimation algorithm; convergence properties; covariance matrix; eigenvectors; fast algorithm; maximum likelihood approach; moving sources localization; orthonormality; signal processing; Computational efficiency; Constraint optimization; Costs; Covariance matrix; Direction of arrival estimation; Eigenvalues and eigenfunctions; Frequency estimation; Maximum likelihood estimation; Signal processing algorithms; Stochastic processes;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.604636
