Multi-Frequency Entropy for Quantifying Complex Dynamics and Its Application on EEG Data

Multi-Frequency Entropy for Quantifying Complex Dynamics and Its Application on EEG Data

Multivariate entropy algorithms have proven effective in the complexity dynamic analysis of electroencephalography (EEG) signals, with researchers commonly configuring the variables as multi-channel time series. However, the complex quantification of brain dynamics from a multi-frequency perspective...

Full description

Saved in:
Bibliographic Details
Main Authors: Yan Niu, Jie Xiang, Kai Gao, Jinglong Wu, Jie Sun, Bin Wang, Runan Ding, Mingliang Dou, Xin Wen, Xiaohong Cui, Mengni Zhou
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:Entropy
Subjects:
multi-frequency entropy
electroencephalography
multivariate entropy
nonlinear time series
complex dynamics
Online Access:https://www.mdpi.com/1099-4300/26/9/728
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items