New Epilepsy Research from China University of Mining and Technology Outlined (Low-rank Sparse Representation-based Transition Subspace Learning Algorithm For Epileptic Seizure Recognition).
| Zdroj: | Health & Medicine Week; 9/13/2024, p3341-3341, 1p |
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| Abstrakt: | A new report discusses research on epilepsy conducted by China University of Mining and Technology. The study focuses on the use of electroencephalogram (EEG) signals as a diagnostic tool for epilepsy. The researchers developed a low-rank sparse representation-based transition subspace learning (LRSRTS) algorithm that aligns multiple domains and separates noise information in the subspace. The algorithm demonstrates satisfactory recognition performance on the CHB-MIT dataset. Further information on the research can be obtained from the authors. [Extracted from the article] |
| Databáze: | Supplemental Index |
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