Generalized Turbo Signal Recovery for Nonlinear Measurements and Orthogonal Sensing Matrices
Information Theory
2016-11-17 v4 math.IT
Abstract
In this study, we propose a generalized turbo signal recovery algorithm to estimate a signal from quantized measurements, in which the sensing matrix is a row-orthogonal matrix, such as the partial discrete Fourier transform matrix. The state evolution of the proposed algorithm is derived and is shown to be consistent with that obtained with the replica method. Numerical experiments illustrate the excellent agreement of the proposed algorithm with theoretical state evolution.
Keywords
Cite
@article{arxiv.1512.04833,
title = {Generalized Turbo Signal Recovery for Nonlinear Measurements and Orthogonal Sensing Matrices},
author = {Ting Liu and Chao-Kai Wen and Shi Jin and Xiaohu You},
journal= {arXiv preprint arXiv:1512.04833},
year = {2016}
}
Comments
To appear in the 2016 IEEE International Symposium on Information Theory (ISIT 2016)