Multi-source manifold feature transfer learning with domain selection for brain-computer interfaces

Author:

She Qingshan,Cai Yinhao,Du Shengzhi,Chen Yun

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Zhejiang Provincial Government Scholarship

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference47 articles.

1. Brain–machine interfaces from motor to mood;Shanechi;Nature Neurosci.,2019

2. T.J.C. Limchesing, A.E.C. Chua, C.J.L. Shi, R.G. Baldovino, F.E.T. Munsayac, N.T. Bugtai, A review on recent applications of eeg-based bci in wheelchairs and other assistive devices, in: 2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), IEEE, 2021, pp. 1–6.

3. Brain-computer interfacing: an introduction;Rao,2013

4. Sub-band target alignment common spatial pattern in brain-computer interface;Zhang;Comput. Methods Programs Biomed.,2021

5. H. Cheng, Z. Wang, Z. Wei, L. Ma, X. Liu, On adaptive learning framework for deep weighted sparse autoencoder: A multiobjective evolutionary algorithm, IEEE Transactions on Cybernetics.

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