A fast algorithm for signal subspace decomposition and its performance analysis
- 1 January 1991
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 3069-3072 vol.5
- https://doi.org/10.1109/icassp.1991.150103
Abstract
A fast signal-subspace decomposition (FSD) algorithm is presented for sample covariance matrices, which only needs O(M/sup 2/d) flops, where d(<<M) denotes the signal subspace dimension. A theoretical performance analysis was conducted, and it shows the strong consistency of the estimation of d and the asymptotic equivalence between the FSD estimate and the one obtained from an eigendecomposition. The approach can be easily implemented in parallel to further reduce the computation time to as little as O(Md) or O(log Md) by using O(M) or O(M/sup 2/) multipliers, respectively.Keywords
This publication has 3 references indexed in Scilit:
- Detection of signals by information theoretic criteriaIEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
- Asymptotic Theory for Principal Component AnalysisThe Annals of Mathematical Statistics, 1963
- An iteration method for the solution of the eigenvalue problem of linear differential and integral operatorsJournal of Research of the National Bureau of Standards, 1950