On the resilience of modern power systems: A complex network perspective
X Ma, H Zhou, Z Li - Renewable and Sustainable Energy Reviews, 2021 - Elsevier
This paper provides a compressive literature review on the application of complex network
theories in the resilience evaluation and enhancement of modern power systems. First, the …
theories in the resilience evaluation and enhancement of modern power systems. First, the …
[HTML][HTML] Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning
Background Wide-field calcium imaging (WFCI) allows for monitoring of cortex-wide neural
dynamics in mice. When applied to the study of sleep, WFCI data are manually scored into …
dynamics in mice. When applied to the study of sleep, WFCI data are manually scored into …
Dynamical graph neural network with attention mechanism for epilepsy detection using single channel EEG
Y Li, Y Yang, Q Zheng, Y Liu, H Wang, S Song… - Medical & Biological …, 2024 - Springer
Epilepsy is a chronic brain disease, and identifying seizures based on
electroencephalogram (EEG) signals would be conducive to implement interventions to help …
electroencephalogram (EEG) signals would be conducive to implement interventions to help …
A review of visibility graph analysis
H Azizi, S Sulaimany - IEEE Access, 2024 - ieeexplore.ieee.org
A graph approach to time series data provides a new perspective for analyzing and
comprehending the characteristics of the data. One common method of converting time …
comprehending the characteristics of the data. One common method of converting time …
L-Tetrolet pattern-based sleep stage classification model using balanced EEG datasets
Background: Sleep stage classification is a crucial process for the diagnosis of sleep or
sleep-related diseases. Currently, this process is based on manual electroencephalogram …
sleep-related diseases. Currently, this process is based on manual electroencephalogram …
Weighted vector visibility based graph signal processing (WVV-GSP) for neural decoding of motor imagery EEG signals
The paper deals with weighted vector visibility-based graph signal processing (WVV-GSP)
to decode motor imagery tasks from multi-channel EEG signals, which plays a key role in …
to decode motor imagery tasks from multi-channel EEG signals, which plays a key role in …
[PDF][PDF] 时间序列复杂网络分析中的可视图方法研究综述
李海林， 王杰， 周文浩， 蔡煜， 林伟滨 - 电子学报, 2023 - ejournal.org.cn
可视图是将时间序列转换成复杂网络的重要方法之一, 也是连接非线性信号分析和复杂网络之间
的全新视角, 在经济金融, 生物医学, 工业工程等领域均应用广泛. 可视图的拓扑结构继承了原始 …
的全新视角, 在经济金融, 生物医学, 工业工程等领域均应用广泛. 可视图的拓扑结构继承了原始 …