Consistency of the Bayes method for the inverse scattering problem with randomly truncated sieve priors
Journal
Inverse Problems and Imaging
Journal Volume
21
Journal Issue
0
Start Page
222
End Page
244
ISSN
1930-8337
1930-8345
Date Issued
2026
Author(s)
Abstract
In this work, we consider the inverse scattering problem of determining an unknown refractive index from the far-field measurements using the nonparametric Bayesian approach. This paper is a continuation of our previous work [5] in which we consider Gaussian priors and Gaussian sieve priors. In this work, we will extend the result to randomly truncated Gaussian sieve priors. Our aim is to establish the consistency of the posterior distribution with an explicit contraction rate in terms of the sample size. Numerical simulations are also provided to justify the theoretical result.
Publisher
American Institute of Mathematical Sciences (AIMS)
Type
journal article