An efficient CNN-LSTM network with spectral normalization and label smoothing technologies for SSVEP frequency recognition.

Pan, Yudong; Chen, Jianbo; Zhang, Yangsong; Zhang, Yu

Pan, Yudong; Chen, Jianbo; Zhang, Yangsong; Zhang, Yu.

Afiliación

Pan Y; Laboratory for Brain Science and Medical Artificial Intelligence,School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, People's Republic of China.
Chen J; Laboratory for Brain Science and Medical Artificial Intelligence,School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, People's Republic of China.
Zhang Y; Laboratory for Brain Science and Medical Artificial Intelligence,School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, People's Republic of China.
Zhang Y; MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, People's Republic of China.

J Neural Eng ; 19(5)2022 09 12.

Article en En | MEDLINE | ID: mdl-36041426

Asunto(s)

Interfaces Cerebro-Computador; Potenciales Evocados Visuales; Algoritmos; Electroencefalografía/métodos; Redes Neurales de la Computación; Estimulación Luminosa/métodos

Palabras clave

convolutional neural network (CNN); label smoothing; long short-term memory (LSTM); spectral normalization; steady-state visual evoked potentials (SSVEPs)

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Potenciales Evocados Visuales / Interfaces Cerebro-Computador Idioma: En Revista: J Neural Eng Asunto de la revista: NEUROLOGIA Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido

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