An a posteriori parameter choice for ordinary and iterated Tikhonov regularization of ill-posed problems leading to optimal convergence rates

Helmut Gfrerer

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Source: Crossref

Published: Jan 1, 1987

DOI: 10.1090/s0025-5718-1987-0906185-4

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Source abstract

We propose an a posteriori parameter choice for ordinary and iterated Tikhonov regularization that leads to optimal rates of convergence towards the best approximate solution of an ill-posed linear operator equation in the presence of noisy data. Numerical examples are given.

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