On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices

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.

to appear in IEEE Signal Processing Letters

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• Towards Designing Optimal Sensing Matrices for Generalized Linear Inverse Problems