A Sparsity Preestimated Adaptive Matching Pursuit Algorithm
In the matching pursuit algorithm of compressed sensing, the traditional reconstruction algorithm needs to know the signal sparsity. The sparsity adaptive matching pursuit (SAMP) algorithm can adaptively approach the signal sparsity when the sparsity is unknown. However, the SAMP algorithm starts fr...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2021/5598180 |
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| author | Xinhe Zhang Yufeng Liu Xin Wang |
| author_facet | Xinhe Zhang Yufeng Liu Xin Wang |
| author_sort | Xinhe Zhang |
| collection | DOAJ |
| description | In the matching pursuit algorithm of compressed sensing, the traditional reconstruction algorithm needs to know the signal sparsity. The sparsity adaptive matching pursuit (SAMP) algorithm can adaptively approach the signal sparsity when the sparsity is unknown. However, the SAMP algorithm starts from zero and iterates several times with a fixed step size to approximate the true sparsity, which increases the runtime. To increase the run speed, a sparsity preestimated adaptive matching pursuit (SPAMP) algorithm is proposed in this paper. Firstly, the sparsity preestimated strategy is used to estimate the sparsity, and then the signal is reconstructed by the SAMP algorithm with the preestimated sparsity as the iterative initial value. The method reconstructs the signal from the preestimated sparsity, which reduces the number of iterations and greatly speeds up the run efficiency. |
| format | Article |
| id | doaj-art-b0a44bff3e39474ea95cb684a0573bd5 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-b0a44bff3e39474ea95cb684a0573bd52025-02-03T01:00:16ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552021-01-01202110.1155/2021/55981805598180A Sparsity Preestimated Adaptive Matching Pursuit AlgorithmXinhe Zhang0Yufeng Liu1Xin Wang2School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, ChinaSchool of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, ChinaSchool of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, ChinaIn the matching pursuit algorithm of compressed sensing, the traditional reconstruction algorithm needs to know the signal sparsity. The sparsity adaptive matching pursuit (SAMP) algorithm can adaptively approach the signal sparsity when the sparsity is unknown. However, the SAMP algorithm starts from zero and iterates several times with a fixed step size to approximate the true sparsity, which increases the runtime. To increase the run speed, a sparsity preestimated adaptive matching pursuit (SPAMP) algorithm is proposed in this paper. Firstly, the sparsity preestimated strategy is used to estimate the sparsity, and then the signal is reconstructed by the SAMP algorithm with the preestimated sparsity as the iterative initial value. The method reconstructs the signal from the preestimated sparsity, which reduces the number of iterations and greatly speeds up the run efficiency.http://dx.doi.org/10.1155/2021/5598180 |
| spellingShingle | Xinhe Zhang Yufeng Liu Xin Wang A Sparsity Preestimated Adaptive Matching Pursuit Algorithm Journal of Electrical and Computer Engineering |
| title | A Sparsity Preestimated Adaptive Matching Pursuit Algorithm |
| title_full | A Sparsity Preestimated Adaptive Matching Pursuit Algorithm |
| title_fullStr | A Sparsity Preestimated Adaptive Matching Pursuit Algorithm |
| title_full_unstemmed | A Sparsity Preestimated Adaptive Matching Pursuit Algorithm |
| title_short | A Sparsity Preestimated Adaptive Matching Pursuit Algorithm |
| title_sort | sparsity preestimated adaptive matching pursuit algorithm |
| url | http://dx.doi.org/10.1155/2021/5598180 |
| work_keys_str_mv | AT xinhezhang asparsitypreestimatedadaptivematchingpursuitalgorithm AT yufengliu asparsitypreestimatedadaptivematchingpursuitalgorithm AT xinwang asparsitypreestimatedadaptivematchingpursuitalgorithm AT xinhezhang sparsitypreestimatedadaptivematchingpursuitalgorithm AT yufengliu sparsitypreestimatedadaptivematchingpursuitalgorithm AT xinwang sparsitypreestimatedadaptivematchingpursuitalgorithm |