A novel iterative method for computing generalized inverse

In this letter, we propose a novel iterative method for computing generalized inverse, based on a novel KKT formulation. The proposed iterative algorithm requires making four matrix and vector multiplications at each iteration and thus has low computational complexity. The proposed method is proved...

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Veröffentlicht in:Neural computation Jg. 26; H. 2; S. 449
Hauptverfasser: Xia, Youshen, Chen, Tianping, Shan, Jinjun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 01.02.2014
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ISSN:1530-888X, 1530-888X
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Zusammenfassung:In this letter, we propose a novel iterative method for computing generalized inverse, based on a novel KKT formulation. The proposed iterative algorithm requires making four matrix and vector multiplications at each iteration and thus has low computational complexity. The proposed method is proved to be globally convergent without any condition. Furthermore, for fast computing generalized inverse, we present an acceleration scheme based on the proposed iterative method. The global convergence of the proposed acceleration algorithm is also proved. Finally, the effectiveness of the proposed iterative algorithm is evaluated numerically.
Bibliographie:ObjectType-Article-1
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ISSN:1530-888X
1530-888X
DOI:10.1162/NECO_a_00549