Denoising recovery for compressive sensing based on selective measure
In order to reduce the effect of noise folding (NF) phenomenon on the performance of sparse signal recon-struction,a new denoising recovery algorithm based on selective measure was proposed.Firstly,the NF phenomenon in compressive sensing (CS) was explained in theory.Secondly,a new statistic based o...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-02-01
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| Series: | Tongxin xuebao |
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| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017033/ |
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| _version_ | 1841539515876900864 |
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| author | Li-ye PEI Hua JIANG Yue-liang MA |
| author_facet | Li-ye PEI Hua JIANG Yue-liang MA |
| author_sort | Li-ye PEI |
| collection | DOAJ |
| description | In order to reduce the effect of noise folding (NF) phenomenon on the performance of sparse signal recon-struction,a new denoising recovery algorithm based on selective measure was proposed.Firstly,the NF phenomenon in compressive sensing (CS) was explained in theory.Secondly,a new statistic based on compressive measurement data was proposed,and its probability density function (PDF) was deduced and analyzed.Then a noise filter matrix was constructed based on the PDF to guide the optimization of measurement matrix.The optimized measurement matrix can selectively sense the sparse signal and suppress the noise to improve the SNR of the measurement data,resulting in the improvement of sparse reconstruction performance.Finally,it was pointed out that increasing the measurement times can further enhance the performance of denoising reconstruction.Simulation results show that the proposed denoising recon-struction algorithm has a better improvement in the performance of reconstruction of noisy signal,especially under low SNR. |
| format | Article |
| id | doaj-art-7af7681d3e3e4c6c88ca2c2f27fc6eb0 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-02-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-7af7681d3e3e4c6c88ca2c2f27fc6eb02025-01-14T07:11:41ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-02-013810611459707370Denoising recovery for compressive sensing based on selective measureLi-ye PEIHua JIANGYue-liang MAIn order to reduce the effect of noise folding (NF) phenomenon on the performance of sparse signal recon-struction,a new denoising recovery algorithm based on selective measure was proposed.Firstly,the NF phenomenon in compressive sensing (CS) was explained in theory.Secondly,a new statistic based on compressive measurement data was proposed,and its probability density function (PDF) was deduced and analyzed.Then a noise filter matrix was constructed based on the PDF to guide the optimization of measurement matrix.The optimized measurement matrix can selectively sense the sparse signal and suppress the noise to improve the SNR of the measurement data,resulting in the improvement of sparse reconstruction performance.Finally,it was pointed out that increasing the measurement times can further enhance the performance of denoising reconstruction.Simulation results show that the proposed denoising recon-struction algorithm has a better improvement in the performance of reconstruction of noisy signal,especially under low SNR.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017033/compressive sensingsignal reconstructionnoise foldingselective measure |
| spellingShingle | Li-ye PEI Hua JIANG Yue-liang MA Denoising recovery for compressive sensing based on selective measure Tongxin xuebao compressive sensing signal reconstruction noise folding selective measure |
| title | Denoising recovery for compressive sensing based on selective measure |
| title_full | Denoising recovery for compressive sensing based on selective measure |
| title_fullStr | Denoising recovery for compressive sensing based on selective measure |
| title_full_unstemmed | Denoising recovery for compressive sensing based on selective measure |
| title_short | Denoising recovery for compressive sensing based on selective measure |
| title_sort | denoising recovery for compressive sensing based on selective measure |
| topic | compressive sensing signal reconstruction noise folding selective measure |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017033/ |
| work_keys_str_mv | AT liyepei denoisingrecoveryforcompressivesensingbasedonselectivemeasure AT huajiang denoisingrecoveryforcompressivesensingbasedonselectivemeasure AT yueliangma denoisingrecoveryforcompressivesensingbasedonselectivemeasure |