Threshold extension of SVD-based algorithms
- 6 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 15206149,p. 2825-2828
- https://doi.org/10.1109/icassp.1988.197240
Abstract
Threshold computation is essential in comparing the statistical performance of algorithms when estimating signal parameters. The authors show that it is possible to extend the threshold effect of singular-value-decomposition (SVD)-based signal-processing algorithms by using the Prony-Lanczos (P-L) method to lower values of signal-to-noise ratio. The procedure is comprised of two steps. In the first step, a nonparametric spectrum analysis or beamforming is used to yield a good starting point. This is followed in the second step by the (P-L) algorithm, which performs a local search, a procedure relatively insensitive to outliers. Simulation results, based on the angles between the estimated and true subspaces using the SVD-based algorithm and the P-L method, provide valuable insight.Keywords
This publication has 5 references indexed in Scilit:
- Improved spectral resolution IIPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Simple, effective computation of principal eigenvectors and their eigenvalues and application to high-resolution estimation of frequenciesIEEE Transactions on Acoustics, Speech, and Signal Processing, 1986
- Spectrum estimation and harmonic analysisProceedings of the IEEE, 1982
- Estimation of frequencies of multiple sinusoids: Making linear prediction perform like maximum likelihoodProceedings of the IEEE, 1982
- Single tone parameter estimation from discrete-time observationsIEEE Transactions on Information Theory, 1974