The Multi-Frequency Decomposition Entropy Learning for Nonlinear fMRI Data Analysis
Functional magnetic resonance imaging (fMRI) have been widely adopted to explore the underlying neural mechanisms between psychiatric disorders which share common neurobiology and clinical manifestations. However, the existing studies mainly focus on linear relationships and ignore nonlinear contrib...
Saved in:
| Main Authors: | Di Han, Yuhu Shi, Lei Wang, Yueyang Li, Weiming Zeng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10793239/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
NONLINEAR ANALYSIS OF BEARING SIGNAL BASED ON IMPROVED VARIATIONAL MODAL DECOMPOSITION AND MUTI FRACTAL
by: JIN JiangTao, et al.
Published: (2022-01-01) -
Gearbox Fault Diagnosis Based on Adaptive Variational Mode Decomposition–Stationary Wavelet Transform and Ensemble Refined Composite Multiscale Fluctuation Dispersion Entropy
by: Xiang Wang, et al.
Published: (2024-11-01) -
Some functionals for copulas
by: C. Alsina, et al.
Published: (1991-01-01) -
Exploring brain dysfunction in IBD: A study of EEG-fMRI source imaging based on empirical mode diagram decomposition
by: Yujie Kang, et al.
Published: (2025-03-01) -
Application of Variational Mode Decomposition based on the FOA and in Bearing Fault Diagnosis
by: Chang Liu, et al.
Published: (2020-05-01)