Sparse measures with swarm-based pliable hidden Markov model and deep learning for EEG classification

Sparse measures with swarm-based pliable hidden Markov model and deep learning for EEG classification

In comparison to other biomedical signals, electroencephalography (EEG) signals are quite complex in nature, so it requires a versatile model for feature extraction and classification. The structural information that prevails in the originally featured matrix is usually lost when dealing with standa...

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Bibliographic Details
Main Authors: Sunil Kumar Prabhakar, Young-Gi Ju, Harikumar Rajaguru, Dong-Ok Won
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Computational Neuroscience
Subjects:
EEG
sparse representation
hidden Markov model
swarm intelligence
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fncom.2022.1016516/full

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