A Statistical view of Iterative Methods for Linear Inverse Problems

Details A Statistical view of Iterative Methods for Linear Inverse Problems A Statistical view of Iterative Methods for Linear Inverse Problems

2005-04-04

arxiv.org/abs/math/0504064v1

Mathematics

Statistics Theory

21 pages

Scientific paper

In this article we study the problem of recovering the unknown solution of a linear ill-posed problem, via iterative regularization methods. We review the problem of projection-regularization from a statistical point of view. A basic purpose of the paper is the consideration of adaptive model selection for determining regularization parameters. This article introduces a new regularized estimator which has the best possible adaptive properties for a wide range of linear functionals. We derive non asymptotic upper bounds for the mean square error of the estimator and give the optimal convergence rates.

Affiliated with

Also associated with

No associations

Rating

A Statistical view of Iterative Methods for Linear Inverse Problems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Statistical view of Iterative Methods for Linear Inverse Problems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Statistical view of Iterative Methods for Linear Inverse Problems will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-576020