Volume 51, pp. 412-431, 2019.

Augmented GMRES-type versus CGNE methods for the solution of linear ill-posed problems

Andreas Neubauer


In this paper we compare (augmented) GMRES-type methods and (augmented) CGNE methods. The numerical results show that the CGNE method is more robust and suitable for ill-posed problems with a much higher degree of ill-posedness. GMRES-type methods only yield useful results for very moderately ill-posed problems.

Full Text (PDF) [408 KB], BibTeX

Key words

(augmented) CGNE and GMRES-type methods

AMS subject classifications

65J20, 65R20, 65R30

Links to the cited ETNA articles

[7]Vol. 42 (2014), pp. 136-146 Yiqiu Dong, Henrik Garde, and Per Christian Hansen: R$^3$GMRES: Including Prior Information in GMRES-Type Methods for Discrete Inverse Problems

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