Efficient Algorithms for Solution of Regularized Total Least Squares

Error-contaminated systems $Ax \approx b$, for which A is ill-conditioned, are considered. Such systems may be solved using Tikhonov-like regularized total least squares (RTLS) methods. Golub, Hansen, and O'Leary [SIAM J. Matrix Anal. Appl., 21 (1999), pp. 185--194] presented a parameter-depend...

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Veröffentlicht in:	SIAM journal on matrix analysis and applications Jg. 26; H. 2; S. 457 - 476
Hauptverfasser:	Renaut, Rosemary A., Guo, Hongbin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2004
Schlagworte:	Algebra Algorithms Alzheimer's disease Eigenvalues Exact sciences and technology Linear and multilinear algebra, matrix theory Mathematics Numerical analysis Numerical analysis. Scientific computation Numerical linear algebra Sciences and techniques of general use Rayleigh quotient Lagrangian Error estimation total least squares Error in variable ill-posedness Iterative method Iteration Modeling Search algorithm Numerical analysis Least squares method 65F30 Linear algebra Rayleigh quotient iteration 65F22 Ill posed problem Eigenvalue problem Quotient Regularization Algorithm analysis Numerical convergence
ISSN:	0895-4798, 1095-7162
Online-Zugang:	Volltext
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