The constrained conjugate gradient algorithm

The constrained conjugate gradient algorithm

Based on the condition for equivalence between linearly constrained minimum-variance (LCMV) filters and their generalized sidelobe canceler (GSC) implementations, we derive the new constrained conjugate gradient (CCG) algorithm. We discuss the use of orthogonal and nonorthogonal blocking matrices fo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE signal processing letters 2000-12, Vol.7 (12), p.351-354
Hauptverfasser: Apolinario, J.A., De Campos, M.L.R., Bernal O, C.P.
Format: Artikel
Sprache:eng
Schlagworte:
Adaptive algorithms
Adaptive filters
Algorithms
Conjugate gradients
Constraints
Finite impulse response filter
Interference constraints
Least squares approximation
Mathematical analysis
Matrices
Matrix decomposition
Minimization methods
Nonlinear filters
Sensor arrays
Sidelobes
Signal processing
Signal processing algorithms
Subspace constraints
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Based on the condition for equivalence between linearly constrained minimum-variance (LCMV) filters and their generalized sidelobe canceler (GSC) implementations, we derive the new constrained conjugate gradient (CCG) algorithm. We discuss the use of orthogonal and nonorthogonal blocking matrices for the GSC structure and how the choice of this matrix may affect the relationship with the LCMV counterpart. The newly derived algorithm was tested in a computer experiment for adaptive multiuser detection and showed excellent results.
ISSN:1070-9908
1558-2361
DOI:10.1109/97.883366