2010/08/03 by Bauer, Frank
#47A52 #60G99 #62H12 #65J22 #FOS: Mathematics #Numerical Analysis (math.NA)
paper · doi:10.48550/arxiv.1008.0620
Choosing the regularization parameter for inverse problems is of major importance for the performance of the regularization method. We will introduce a fast version of the Lepskij balancing principle and show that it is a valid parameter choice method for Tikhonov regularization both in a deterministic and a stochastic noise regime as long as minor conditions on the solution are fulfilled.