S-AMP for Non-linear Observation Models
Information Theory
2015-01-27 v1 math.IT
Abstract
Recently we extended Approximate message passing (AMP) algorithm to be able to handle general invariant matrix ensembles. In this contribution we extend our S-AMP approach to non-linear observation models. We obtain generalized AMP (GAMP) algorithm as the special case when the measurement matrix has zero-mean iid Gaussian entries. Our derivation is based upon 1) deriving expectation propagation (EP) like algorithms from the stationary-points equations of the Gibbs free energy under first- and second-moment constraints and 2) applying additive free convolution in free probability theory to get low-complexity updates for the second moment quantities.
Cite
@article{arxiv.1501.06216,
title = {S-AMP for Non-linear Observation Models},
author = {Burak Çakmak and Ole Winther and Bernard H. Fleury},
journal= {arXiv preprint arXiv:1501.06216},
year = {2015}
}
Comments
6 pages