Multiscale transfer spectral entropy for quantifying corticomuscular interaction

2020 ◽  
pp. 1-1
Author(s):  
Jinbiao Liu ◽  
Gansheng Tan ◽  
Yixuan Sheng ◽  
Honghai Liu
Keyword(s):  
Spectral Entropy

Sudden decrease in spectral entropy associated with severe carotid artery spasm

2009 ◽  
Vol 26 (1) ◽  
pp. 84-86 ◽  
Author(s):  
Sriganesh Kamath ◽  
Puthuvassery Raman Suneel ◽  
Subrata Kumar Singha
Keyword(s):  
Carotid Artery ◽  
Spectral Entropy ◽  
Sudden Decrease

scholarly journals Correlation of EEG spectral entropy with regional cerebral blood flow during sevoflurane and propofol anaesthesia

Anaesthesia ◽  
2005 ◽  
Vol 60 (9) ◽  
pp. 862-869 ◽  
Author(s):  
A. Maksimow ◽  
K. Kaisti ◽  
S. Aalto ◽  
M. Mäenpää ◽  
S. Jääskeläinen ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Regional Cerebral Blood Flow ◽  
Spectral Entropy ◽  
Regional Cerebral Blood

Effects of the electric drill in accuracy of spectral entropy in tympanoplasty

2005 ◽  
Vol 22 (Supplement 34) ◽  
pp. 26
Author(s):  
R. Villazala ◽  
M. Zaballos ◽  
A. Varela ◽  
P. Carmona ◽  
A. Yuste
Keyword(s):  
Spectral Entropy ◽  
Electric Drill

scholarly journals A Hidden Chaotic System with Multiple Attractors

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1341
Author(s):  
Xiefu Zhang ◽  
Zean Tian ◽  
Jian Li ◽  
Xianming Wu ◽  
Zhongwei Cui
Keyword(s):  
Phase Diagram ◽  
Lyapunov Exponent ◽  
Numerical Methods ◽  
Chaotic System ◽  
Time Domain ◽  
Chaotic Attractor ◽  
Largest Lyapunov Exponent ◽  
Spectral Entropy ◽  
Multiple Attractors ◽  
System Parameters

This paper reports a hidden chaotic system without equilibrium point. The proposed system is studied by the software of MATLAB R2018 through several numerical methods, including Largest Lyapunov exponent, bifurcation diagram, phase diagram, Poincaré map, time-domain waveform, attractive basin and Spectral Entropy. Seven types of attractors are found through altering the system parameters and some interesting characteristics such as coexistence attractors, controllability of chaotic attractor, hyperchaotic behavior and transition behavior are observed. Particularly, the Spectral Entropy algorithm is used to analyze the system and based on the normalized values of Spectral Entropy, the state of the studied system can be identified. Furthermore, the system has been implemented physically to verify the realizability.

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