On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices
Information Theory
2016-11-15 v1 math.IT
Abstract
This letter is on the performance of the turbo signal recovery (TSR) algorithm for partial discrete Fourier transform (DFT) matrices based compressed sensing. Based on state evolution analysis, we prove that TSR with a partial DFT sensing matrix outperforms the well-known approximate message passing (AMP) algorithm with an independent identically distributed (IID) sensing matrix.
Keywords
Cite
@article{arxiv.1503.05314,
title = {On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices},
author = {Junjie Ma and Xiaojun Yuan and Li Ping},
journal= {arXiv preprint arXiv:1503.05314},
year = {2016}
}
Comments
to appear in IEEE Signal Processing Letters