Solve Mismatch Problem in Compressed Sensing
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910677785903104 |
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| author | Yang, Le |
| author_facet | Yang, Le |
| contents | 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 |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_22354 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Solve Mismatch Problem in Compressed Sensing Yang, Le Signal Processing Information Theory 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 |
| title | Solve Mismatch Problem in Compressed Sensing |
| topic | Signal Processing Information Theory |
| url | https://arxiv.org/abs/2410.22354 |