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Deep convolutional neural networks and power spectral density features for motor imagery classification of EEG signals

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Deep convolutional neural networks and power spectral density features for motor imagery classification of EEG signals
Date
2018
Author
Pérez-Zapata A.F.
Cardona-Escobar A.F.
Jaramillo-Garzón J.A.
Díaz G.M.

Citation

       
TY - GEN T1 - Deep convolutional neural networks and power spectral density features for motor imagery classification of EEG signals AU - Pérez-Zapata A.F. AU - Cardona-Escobar A.F. AU - Jaramillo-Garzón J.A. AU - Díaz G.M. Y1 - 2018 UR - http://hdl.handle.net/20.500.12622/3382 AB - ER - @misc{20.500.12622_3382, author = {Pérez-Zapata A.F. and Cardona-Escobar A.F. and Jaramillo-Garzón J.A. and Díaz G.M.}, title = {Deep convolutional neural networks and power spectral density features for motor imagery classification of EEG signals}, year = {2018}, abstract = {}, url = {http://hdl.handle.net/20.500.12622/3382} }RT Generic T1 Deep convolutional neural networks and power spectral density features for motor imagery classification of EEG signals A1 Pérez-Zapata A.F. A1 Cardona-Escobar A.F. A1 Jaramillo-Garzón J.A. A1 Díaz G.M. YR 2018 LK http://hdl.handle.net/20.500.12622/3382 AB OL Spanish (121)
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050588425&doi=10.1007%2f978-3-319-91470-1_14&partnerID=40&md5=fcc2cf2a951887880e7002823f677d5a
URI
http://hdl.handle.net/20.500.12622/3382
DOI
https://doi.org/10.1007/978-3-319-91470-1_14
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