Paper Info
Title
Deep View-Reduction TSK Fuzzy System: A Case Study on Epileptic EEG Signals Detection
Abstract
In many practical applications, the fuzzy systems have been used due to the promising approximation accuracy and the high interpretability. Here, we proposed a novel multiview Takagi-Sugeno-Kang (TSK) fuzzy system in which a deep structure associating with a view-reduction mechanism are involved. The deep structure of each view is constructed by many basic components, i.e., the classic one-order TSK fuzzy systems which are linked in a layer by layer way using the stacked generalization principle. The view-reduction mechanism contains two parts: 1) A user-free parameter which is fixed according to the feature distribution is introduced to guild the view weight learning; 2) Views with noisy weights are automatically filtered by a reduction principle which is generated according to the training data. The proposed multi-view fuzzy system is finally applied for epileptic EEG signals detection.
Year
DOI
Venue
2019
10.1109/SSCI44817.2019.9002722
2019 IEEE Symposium Series on Computational Intelligence (SSCI)
Keywords
Field
DocType
TSK fuzzy systems,multi-view learning,stacked generalization principle,view reduction
Training set,Interpretability,Pattern recognition,Computer science,Artificial intelligence,Fuzzy control system,Electroencephalography
Conference
ISBN
Citations 
PageRank 
978-1-7281-2486-5
0
0.34
References 
Authors
7
3
Name
Order
Citations
PageRank
Ziyuan Zhou100.34
Yuanpeng Zhang200.34
Yizhang Jiang338227.24