An Adaptive EEG Feature Extraction Method Based on Stacked Denoising Autoencoder for Mental Fatigue Connectivity
Mental fatigue is a common psychobiological state elected by prolonged cognitive activities. Although, the performance and the disadvantage of the mental fatigue have been well known, its connectivity among the multiareas of the brain has not been thoroughly studied yet. This is important for the cl...
Saved in:
Main Authors: | Zhongliang Yu, Lili Li, Wenwei Zhang, Hangyuan Lv, Yun Liu, Umair Khalique |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | Neural Plasticity |
Online Access: | http://dx.doi.org/10.1155/2021/3965385 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Classification of Thyroid Nodules with Stacked Denoising Sparse Autoencoder
by: Zexin Li, et al.
Published: (2020-01-01) -
Smart Shift Decision Method Based on Stacked Autoencoders
by: Zengcai Wang, et al.
Published: (2018-01-01) -
EEG-to-EEG: Scalp-to-Intracranial EEG Translation Using a Combination of Variational Autoencoder and Generative Adversarial Networks
by: Bahman Abdi-Sargezeh, et al.
Published: (2025-01-01) -
Data-Driven Bearing Fault Diagnosis of Microgrid Network Power Device Based on a Stacked Denoising Autoencoder in Deep Learning and Clustering by Fast Search without Data Labels
by: Fan Xu, et al.
Published: (2020-01-01) -
Moisture Content Quantization of Masson Pine Seedling Leaf Based on Stacked Autoencoder with Near-Infrared Spectroscopy
by: Chao Ni, et al.
Published: (2018-01-01)