دورية أكاديمية
A Hybrid Approach for Fast Computation of Multiple Incident Angles Electromagnetic Scattering Problems with Compressive Sensing and Adaptive Cross Approximation
العنوان: | A Hybrid Approach for Fast Computation of Multiple Incident Angles Electromagnetic Scattering Problems with Compressive Sensing and Adaptive Cross Approximation |
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المؤلفون: | Guo-hua Wang, Yu-fa Sun |
المصدر: | International Journal of Antennas and Propagation, Vol 2016 (2016) |
بيانات النشر: | Hindawi Limited, 2016. |
سنة النشر: | 2016 |
المجموعة: | LCC:Electrical engineering. Electronics. Nuclear engineering |
مصطلحات موضوعية: | Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Cellular telephone services industry. Wireless telephone industry, HE9713-9715 |
الوصف: | A hybrid compressive approach for fast computation of the electromagnetic scattering problems with multiple incident angles is proposed. The compressive sensing (CS) technique is firstly introduced to the method of moment (MoM) to reduce the number of the right-hand sides (RHS), but since the resulting excitation matrix contains linear dependency and has low-rank characteristics, the adaptive cross approximation (ACA) algorithm is used to recompress such excitation matrix, keeping only the necessary physical information. The hybrid compressive approach can reduce the number of the RHS to lower level. In fact, the ratio of the number of the RHS between the compressed excitation matrix and the original excitation matrix in the conventional MoM is close to one to fifteen. Numerical results are presented to validate the efficiency and accuracy of this method, which turns out to be highly efficient and accurate for the solution to multiple incident angles electromagnetic scattering problems. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 1687-5869 1687-5877 |
العلاقة: | https://doaj.org/toc/1687-5869Test; https://doaj.org/toc/1687-5877Test |
DOI: | 10.1155/2016/1416094 |
الوصول الحر: | https://doaj.org/article/bcc55ad1cc844dcba7a3fc35ea17782cTest |
رقم الانضمام: | edsdoj.bcc55ad1cc844dcba7a3fc35ea17782c |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 16875869 16875877 |
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DOI: | 10.1155/2016/1416094 |