Optimal Convergence of the Discrepancy Principle for polynomially and exponentially ill-posed Operators under White Noise
Abstract
We consider a linear ill-posed equation in the Hilbert space setting under white noise. Known convergence results for the discrepancy principle are either restricted to Hilbert-Schmidt operators (and they require a self-similarity condition for the unknown solution , additional to a classical source condition) or to polynomially ill-posed operators (excluding exponentially ill-posed problems). In this work we show optimal convergence for a modified discrepancy principle for both polynomially and exponentially ill-posed operators (without further restrictions) solely under either H\"older-type or logarithmic source conditions. In particular, the method includes only a single simple hyper parameter, which does not need to be adapted to the type of ill-posedness.
Keywords
Cite
@article{arxiv.2104.06184,
title = {Optimal Convergence of the Discrepancy Principle for polynomially and exponentially ill-posed Operators under White Noise},
author = {Tim Jahn},
journal= {arXiv preprint arXiv:2104.06184},
year = {2021}
}