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- W1467977892 abstract "In this paper, we present new perturbation analysis and randomized algorithms for the total least squares (Tls) problem. Our new perturbation results are sharper than the earlier ones. We prove that the condition numbers obtained by Zhou et al. [Numer. Algorithm, 51 (2009), pp. 381-399], Barboulin and Gratton [SIAM J. Matrix Anal. Appl., 32 (2011), pp. 685-699], Li and Jia [Linear Algebra Appl., 435 (2011), pp. 674-686] are mathematically equivalent. Statistical condition estimates (Sce) are applied to the Tls problem. Motivated by the recently popular probabilistic algorithms for low-rank approximations, we develop randomized algorithms for the Tls and the truncated total least squares (Ttls) solutions of large-scale discrete ill-posed problems, which can greatly reduce the computational time and still keep good accuracy. Its efficiency is well demonstrated by numerical examples." @default.
- W1467977892 created "2016-06-24" @default.
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- W1467977892 date "2014-01-27" @default.
- W1467977892 modified "2023-09-25" @default.
- W1467977892 title "Statistical Condition Estimates and Randomized Algorithms for Large-Scale Total Least Squares Problems" @default.
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