Solve Mismatch Problem in Compressed Sensing

October 15, 2024 · Entered Twilight · 🏛 arXiv.org

Repo contents: .gitignore, LICENSE, README.md, RESULTS-README.md, __init__.py, assets, calibration-M.ipynb, calibration-N.ipynb, mmf_displacement, mmf_speckle.py, multiply-test.ipynb, nosie.ipynb, recv-exps.ipynb, recv-mismatch.ipynb, results, timg, trad_cs_recv_algos, without-nosie.ipynb

Authors Le Yang arXiv ID 2410.22354 Category eess.SP: Signal Processing Cross-listed cs.IT Citations 0 Venue arXiv.org Repository https://github.com/yanglebupt/mismatch-solution Last Checked 4 months ago

Abstract

This article proposes a novel algorithm for solving mismatch problem in compressed sensing. Its core is to transform mismatch problem into matched by constructing a new measurement matrix to match measurement value under unknown measurement matrix. Therefore, we propose mismatch equation and establish two types of algorithm based on it, which are matched solution of unknown measurement matrix and calibration of unknown measurement matrix. Experiments have shown that when under low gaussian noise levels, the constructed measurement matrix can transform the mismatch problem into matched and recover original images. The code is available: https://github.com/yanglebupt/mismatch-solution