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Regularization, GSVD and Truncated GSVD (Generalized Singular Value Decomposition).

机译：正则化，GsVD和截断GsVD（广义奇异值分解）。

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The generalized singular value decomposition (GSVD) is used to analyze two alternative methods for solving ill-posed problems: regularization in general form, and truncated SVD. We give conditions in which suitable solutions can be found, discuss the perturbation theory, and show that the optimum regularization and truncation parameters can be computed via generalized cross-validation. Our analysis also sheds light on a particular method, based on a transformation to standard form, that avoids the numerical difficulties associated with computation of the GSVD. 15 refs., 1 fig. (ERA citation 13:055982)

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