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Tikhonov regularization of large symmetric problems. (English) Zbl 1164.65377

Summary: Many popular solution methods for large discrete ill-posed problems are based on Tikhonov regularization and compute a partial Lanczos bidiagonalization of the matrix. The computational effort required by these methods is not reduced significantly when the matrix of the discrete ill-posed problem, rather than being a general nonsymmetric matrix, is symmetric and possibly indefinite. This paper describes new methods, based on partial Lanczos tridiagonalization of the matrix, that exploit symmetry. Computed examples (a Fredholm integral equation, image reconstruction) illustrate that these methods can require significantly less computational work than available structure-ignoring schemes.

MSC:

65F22 Ill-posedness and regularization problems in numerical linear algebra
65R20 Numerical methods for integral equations
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
Full Text: DOI

References:

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