Time Series Classification for EEG Eye State Identification Based on Incremental Attribute Learning

2014 ◽  
Author(s):  
Ting Wang ◽  
Sheng Uei Guan ◽  
Ka Lok Man ◽  
T.O. Ting
Keyword(s):  
Time Series ◽  
Time Series Classification ◽  
State Identification ◽  
Attribute Learning

scholarly journals EEG Eye State Identification Using Incremental Attribute Learning with Time-Series Classification

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ting Wang ◽  
Sheng-Uei Guan ◽  
Ka Lok Man ◽  
T. O. Ting
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Hot Spot ◽  
Error Rates ◽  
Classification Error ◽  
Time Series Classification ◽  
Classification Problems ◽  
State Identification ◽  
State Classification ◽  
Attribute Learning

Eye state identification is a kind of common time-series classification problem which is also a hot spot in recent research. Electroencephalography (EEG) is widely used in eye state classification to detect human's cognition state. Previous research has validated the feasibility of machine learning and statistical approaches for EEG eye state classification. This paper aims to propose a novel approach for EEG eye state identification using incremental attribute learning (IAL) based on neural networks. IAL is a novel machine learning strategy which gradually imports and trains features one by one. Previous studies have verified that such an approach is applicable for solving a number of pattern recognition problems. However, in these previous works, little research on IAL focused on its application to time-series problems. Therefore, it is still unknown whether IAL can be employed to cope with time-series problems like EEG eye state classification. Experimental results in this study demonstrates that, with proper feature extraction and feature ordering, IAL can not only efficiently cope with time-series classification problems, but also exhibit better classification performance in terms of classification error rates in comparison with conventional and some other approaches.

A Frequent Pattern Based Time Series Classification Framework

2010 ◽  
Vol 32 (2) ◽  
pp. 261-266
Author(s):  
Li Wan ◽  
Jian-xin Liao ◽  
Xiao-min Zhu ◽  
Ping Ni
Keyword(s):  
Time Series ◽  
Frequent Pattern ◽  
Time Series Classification ◽  
Classification Framework

Time-series classification with an all-optical recurrent neuron

2020 ◽  
Author(s):  
G. Mourgias-Alexandris ◽  
N. Passalis ◽  
G. Dabos ◽  
A. Totovic ◽  
A. Tefas ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Classification ◽  
All Optical

scholarly journals RTFN: A Robust Temporal Feature Network for Time Series Classification

2021 ◽  
Author(s):  
Zhiwen Xiao ◽  
Xin Xu ◽  
Huanlai Xing ◽  
Shouxi Luo ◽  
Penglin Dai ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Classification ◽  
Temporal Feature

scholarly journals A Novel Channel and Temporal-Wise Attention in Convolutional Networks for Multivariate Time Series Classification

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 212247-212257
Author(s):  
Xu Cheng ◽  
Peihua Han ◽  
Guoyuan Li ◽  
Shengyong Chen ◽  
Houxiang Zhang
Keyword(s):  
Time Series ◽  
Multivariate Time Series ◽  
Time Series Classification ◽  
Convolutional Networks
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