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The Use of Multivariate EMD and CCA for Denoising Muscle Artifacts From Few-Channel EEG Recordings.

, , , , and . IEEE Trans. Instrum. Meas., 67 (2): 359-370 (2018)

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A novel few-channel strategy for removing muscle artifacts from multichannel EEG data., , and . GlobalSIP, page 976-980. IEEE, (2017)Supervised Feature Selection With Orthogonal Regression and Feature Weighting., , , , , and . IEEE Trans. Neural Networks Learn. Syst., 32 (5): 1831-1838 (2021)The Recognition of Multiple Anxiety Levels Based on Electroencephalograph., , , , , , and . IEEE Trans. Affect. Comput., 13 (1): 519-529 (2022)Supervised feature selection with orthogonal regression and feature weighting., , , , , and . CoRR, (2019)Embedded Multi-label Feature Selection via Orthogonal Regression., , , , , and . CoRR, (2024)Working Memory Training Using EEG Neurofeedback Based on Theta Coherence of Brain Regions., , , , , and . BCI, page 1-6. IEEE, (2019)A General Framework for Feature Selection Under Orthogonal Regression With Global Redundancy Minimization., , , , and . IEEE Trans. Knowl. Data Eng., 34 (11): 5056-5069 (2022)The Use of Multivariate EMD and CCA for Denoising Muscle Artifacts From Few-Channel EEG Recordings., , , , and . IEEE Trans. Instrum. Meas., 67 (2): 359-370 (2018)EEG Feature Selection via Global Redundancy Minimization for Emotion Recognition., , , , , and . IEEE Trans. Affect. Comput., 14 (1): 421-435 (January 2023)Feature Selection Under Orthogonal Regression with Redundancy Minimizing., and . ICASSP, page 3457-3461. IEEE, (2020)