Extensions of Faddeev’s algorithms to polynomial matrices

Starting from algorithms introduced in [Ky M. Vu, An extension of the Faddeev’s algorithms, in: Proceedings of the IEEE Multi-conference on Systems and Control on September 3–5th, 2008, San Antonio, TX] which are applicable to one-variable regular polynomial matrices, we introduce two dual extension...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Applied mathematics and computation Jg. 214; H. 1; S. 246 - 258
Hauptverfasser: Stanimirović, Predrag S., Tasić, Milan B., Vu, Ky M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier Inc 01.08.2009
Elsevier
Schlagworte:
Drazin inverse
Exact sciences and technology
Leverrier–Faddeev algorithm
MATHEMATICA
Mathematical analysis
Mathematics
Moore–Penrose inverse
Numerical analysis
Numerical analysis. Scientific computation
Polynomial matrices
Sciences and techniques of general use
Drazin inverse
MATHEMATICA
Leverrier–Faddeev algorithm
Moore–Penrose inverse
Polynomial matrices
Polynomial
Numerical analysis
Moore Penrose inverse
Applied mathematics
Leverrier-Faddeev algorithm
Control system
Algorithm
Moore-Penrose inverse
Implementation
ISSN:0096-3003, 1873-5649
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Starting from algorithms introduced in [Ky M. Vu, An extension of the Faddeev’s algorithms, in: Proceedings of the IEEE Multi-conference on Systems and Control on September 3–5th, 2008, San Antonio, TX] which are applicable to one-variable regular polynomial matrices, we introduce two dual extensions of the Faddeev’s algorithm to one-variable rectangular or singular matrices. Corresponding algorithms for symbolic computing the Drazin and the Moore–Penrose inverse are introduced. These algorithms are alternative with respect to previous representations of the Moore–Penrose and the Drazin inverse of one-variable polynomial matrices based on the Leverrier–Faddeev’s algorithm. Complexity analysis is performed. Algorithms are implemented in the symbolic computational package MATHEMATICA and illustrative test examples are presented.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2009.03.076