دورية أكاديمية
Modified complex multitask Bayesian compressive sensing using Laplacian scale mixture prior
| العنوان: | Modified complex multitask Bayesian compressive sensing using Laplacian scale mixture prior |
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| المؤلفون: | Qilei Zhang, Lei Yu, Feng He, Yifei Ji |
| المصدر: | IET Signal Processing, Vol 16, Iss 5, Pp 601-614 (2022) |
| بيانات النشر: | Hindawi-IET, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Telecommunication |
| مصطلحات موضوعية: | Bayes methods, compressed sensing, signal reconstruction, Telecommunication, TK5101-6720 |
| الوصف: | Abstract Bayesian compressive sensing (BCS) is an important sub‐class of sparse signal reconstruction algorithms. In this paper, a modified complex multitask Bayesian compressive sensing (MCMBCS) algorithm using the Laplacian scale mixture (LSM) prior is proposed. The LSM prior is first introduced into the complex BCS framework by exploiting its better sparse characteristic and flexibility than traditional Laplacian prior. Furthermore, by integrating out the noise variance analytically, the MCMBCS algorithm significantly improves the signal recovery performance than the original CMBCS. More importantly, the authors not only present the iterative algorithm but also develop the sub‐optimal fast implementation method based on the marginal likelihood maximisation, which dramatically reduce the computational complexity. Finally, sufficient numerical simulations validate the better performance of the proposed algorithm in reconstruction accuracy and computational effectiveness than existing work. It is revealed that the proposed algorithm has great potential in the complex‐valued signal processing field. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1751-9683 1751-9675 |
| Relation: | https://doaj.org/toc/1751-9675; https://doaj.org/toc/1751-9683 |
| DOI: | 10.1049/sil2.12134 |
| URL الوصول: | https://doaj.org/article/6e0f1c2c363842a4a8684158890defeb |
| رقم الأكسشن: | edsdoj.6e0f1c2c363842a4a8684158890defeb |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 17519683 17519675 |
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| DOI: | 10.1049/sil2.12134 |