دورية أكاديمية
Suppressing the Spikes in Electroencephalogram via an Iterative Joint Singular Spectrum Analysis and Low-Rank Decomposition Approach
| العنوان: | Suppressing the Spikes in Electroencephalogram via an Iterative Joint Singular Spectrum Analysis and Low-Rank Decomposition Approach |
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| المؤلفون: | Zikang Tian, Bingo Wing-Kuen Ling, Xueling Zhou, Ringo Wai-Kit Lam, Kok-Lay Teo |
| المصدر: | Sensors, Vol 20, Iss 2, p 341 (2020) |
| بيانات النشر: | MDPI AG, 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Chemical technology |
| مصطلحات موضوعية: | suppressing the spikes, electroencephalogram, singular spectrum analysis, low-rank decomposition, Chemical technology, TP1-1185 |
| الوصف: | The novelty and the contribution of this paper consists of applying an iterative joint singular spectrum analysis and low-rank decomposition approach for suppressing the spikes in an electroencephalogram. First, an electroencephalogram is filtered by an ideal lowpass filter via removing its discrete Fourier transform coefficients outside the δ wave band, the θ wave band, the α wave band, the β wave band and the γ wave band. Second, the singular spectrum analysis is performed on the filtered electroencephalogram to obtain the singular spectrum analysis components. The singular spectrum analysis components are sorted according to the magnitudes of their corresponding eigenvalues. The singular spectrum analysis components are sequentially added together starting from the last singular spectrum analysis component. If the variance of the summed singular spectrum analysis component under the unit energy normalization is larger than a threshold value, then the summation is terminated. The summed singular spectrum analysis component forms the first scale of the electroencephalogram. The rest singular spectrum analysis components are also summed up together separately to form the residue of the electroencephalogram. Next, the low-rank decomposition is performed on the residue of the electroencephalogram to obtain both the low-rank component and the sparse component. The low-rank component is added to the previous scale of the electroencephalogram to obtain the next scale of the electroencephalogram. Finally, the above procedures are repeated on the sparse component until the variance of the current scale of the electroencephalogram under the unit energy normalization is larger than another threshold value. The computer numerical simulation results show that the spike suppression performance based on our proposed method outperforms that based on the state-of-the-art methods. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1424-8220 20020341 |
| Relation: | https://www.mdpi.com/1424-8220/20/2/341; https://doaj.org/toc/1424-8220 |
| DOI: | 10.3390/s20020341 |
| URL الوصول: | https://doaj.org/article/9b8baf9f8b1f4e28bd9e871352d5e09e |
| رقم الأكسشن: | edsdoj.9b8baf9f8b1f4e28bd9e871352d5e09e |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 14248220 20020341 |
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| DOI: | 10.3390/s20020341 |