Adaptive algorithms for eigenstructure based spectral estimation and filtering
K.C. Sharman, T.S. Durrani, L. Vergara-Dominguez · 1986
This paper considers the problem of adaptive estimation of the complete set of eigenvectors and eigenvalues of a data covariance matrix. After considering some applications of eigenstructure algorithms to spectral estimation and constrained filtering problems, the paper discusses a new approach to data adaptive eigenestimation. A new technique based on an adaptive implementation of the Q-R algorithm is presented. This algorithm offers a strategy for recursive estimation of the complete set of covariance matrix eigenvectors and eigenvalues, which is computationally efficient to implement.