Exploiting the Cone of Influence for Improving the Performance of Wavelet Transform-Based Models for ERP/EEG Classification

Exploiting the Cone of Influence for Improving the Performance of Wavelet Transform-Based Models for ERP/EEG Classification

Features extracted from the wavelet transform coefficient matrix are widely used in the design of machine learning models to classify event-related potential (ERP) and electroencephalography (EEG) signals in a wide range of brain activity research and clinical studies. This novel study is aimed at d...

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Bibliographic Details
Main Authors: Xiaoqian Chen, Resh S. Gupta, Lalit Gupta
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Brain Sciences
Subjects:
event-related potentials
electroencephalography
continuous wavelet transform
scalogram
cone of influence
subsample averaging
Online Access:https://www.mdpi.com/2076-3425/13/1/21

Internet

https://www.mdpi.com/2076-3425/13/1/21

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