Estimation of a signal waveform from noisy data using low-rank approximation to a data matrix

An analysis and improvement of a data-adaptive signal estimation algorithm are presented. Perturbation analysis of a reduced-rank data matrix is used to reveal its statistical properties. The obtained information is used for calculating the performance of the Toeplitz-restoration algorithm of D. Tuf...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on signal processing 1993-04, Vol.41 (4), p.1716-1721
Hauptverfasser: Tufts, D.W., Shah, A.A.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:An analysis and improvement of a data-adaptive signal estimation algorithm are presented. Perturbation analysis of a reduced-rank data matrix is used to reveal its statistical properties. The obtained information is used for calculating the performance of the Toeplitz-restoration algorithm of D. Tufts et al. (1982). This analysis leads to improvements of the methods, and the predicted improvements are demonstrated by simulation and comparison with the Cramer-Rao bounds.< >
ISSN:1053-587X
1941-0476
DOI:10.1109/78.212753