Blind Separation Of Multicomponent Seismic Wavefield Using SVD Of Reduced Dimension Spectral Matrix
| المصدر: | مجلة جامعة الملك سعود - علوم الحاسب والمعلومات |
|---|---|
| الناشر: | جامعة الملك سعود |
| المؤلف الرئيسي: | Al-Hasanat, Abdullah (Author) |
| مؤلفين آخرين: | Mesleh, Abdelwadood (Co-Author), Krishan, Monther (Co-Author), Sharadqh, Ahmed (Co-Author), Al-Qaisi, Aws (Co-Author) |
| المجلد/العدد: | مج29, ع1 |
| محكمة: | نعم |
| الدولة: |
السعودية |
| التاريخ الميلادي: |
2017
|
| الصفحات: | 39 - 53 |
| DOI: |
10.33948/0584-029-001-003 |
| ISSN: |
1319-1578 |
| رقم MD: | 974039 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | science |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Blind Separation | Multicomponent Seismic Wavefield | SVD
|
| رابط المحتوى: |
| المستخلص: |
This paper presents a blind separation algorithm based on singular value decomposition (SVD) of reduced dimension spectral matrix. Furthermore, a mathematical matrix model of the multicomponent seismic wave field is developed as a framework for implementing the proposed algorithm. The proposed blind separation algorithm organizes the frequency transformed multicomponent seismic wave field into one long data vector. The blind separation of the desired seismic wave field is accomplished by projecting the long data vector onto the eigenvectors of the dimensionally reduced spectral matrix according to the energy of the eigenvalues. The proposed algorithm is tested on both synthetic and real multicomponent seismic wave fields. Results show outstanding performance compared to the MC WBSMF algorithm. Therefore, the computational complexity is reduced by a factor greater than 14,400 and there is an improvement in accuracy of 17.5%. |
|---|---|
| ISSN: |
1319-1578 |
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