# Turbo Compressed Sensing with Partial DFT Sensing Matrix

Source: [Turbo Compressed Sensing with Partial DFT Sensing Matrix](<https://www.sota2.com/research/paper/68fa51281e209131ce971687>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T11:15:28.167Z

Authors: Junjie Ma, Xiaojun Yuan, Li Ping

Published: 2014-08-18T06:46:20.000Z

## Abstract

In this letter, we propose a turbo compressed sensing algorithm with partial discrete Fourier transform (DFT) sensing matrices. Interestingly, the state evolution of the proposed algorithm is shown to be consistent with that derived using the replica method. Numerical results demonstrate that the proposed algorithm outperforms the well-known approximate message passing (AMP) algorithm when a partial DFT sensing matrix is involved.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Image Compression on CelebA (test)](<https://www.sota2.com/research/sota/image-compression-on-celeba-test.md>): Image Compression; CelebA (test); PSNR: 33.77.

- [Joint image compression and wireless transmission on CelebA TDL-A channels](<https://www.sota2.com/research/sota/joint-image-compression-and-wireless-transmission-on-celeba-tdl-a-channels.md>): Joint image compression and wireless transmission; CelebA TDL-A channels; PSNR: 31.32.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1408.3904>)

[PDF](<https://arxiv.org/pdf/1408.3904.pdf>)