A Fusion Dimension Reduction Method for the Features of Surface Electromyographic Signals
Surface electromyographic signals (sEMG) usually have high-dimensional properties, and direct processing of these data consumes significant computational resources. Dimensionality reduction processing can reduce the dimension of the data and improve the real-time performance and response speed. This...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10731713/ |
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