Visibility Graph from Adaptive Optimal Kernel Time-Frequency Representation for Classification of Epileptiform EEG
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ID: 269213
2017
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Abstract
Detecting epileptic seizure from EEG signals constitutes a challenging problem of significant importance. Combining adaptive optimal kernel time-frequency representation and visibility graph, we develop a novel method for detecting epileptic seizure from EEG signals. We construct complex networks fr …
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| Reference Key |
zk2017internationalvisibility
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|---|---|
| Authors | Gao ZK;Cai Q;Yang YX;Dong N;Zhang SS;; |
| Journal | international journal of neural systems |
| Year | 2017 |
| DOI |
DOI not found
|
| URL | |
| Keywords |
National Center for Biotechnology Information
NCBI
NLM
MEDLINE
humans
pubmed abstract
nih
national institutes of health
national library of medicine
algorithms
computer-assisted*
time factors
signal processing
cluster analysis
brain / diagnostic imaging*
brain / physiopathology
pmid:27832712
doi:10.1142/s0129065717500058
zhong-ke gao
qing cai
shan-shan zhang
datasets as topic
electroencephalography / methods*
entropy
epilepsy / diagnostic imaging*
epilepsy / physiopathology
neural pathways / diagnostic imaging
neural pathways / physiopathology
seizures / diagnostic imaging
seizures / physiopathology
|
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