scholarly journals The Bivariate Empirical Mode Decomposition and Its Contribution to Grinding Chatter Detection

2017 ◽  
Vol 7 (2) ◽  
pp. 145 ◽  
Author(s):  
Huanguo Chen ◽  
Jianyang Shen ◽  
Wenhua Chen ◽  
Chuanyu Wu ◽  
Chunshao Huang ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Chatter Detection ◽  
Grinding Chatter ◽  
Mode Decomposition ◽  
Bivariate Empirical Mode Decomposition

Automated Classification of Focal and Non-Focal EEG Signals Based on Bivariate Empirical Mode Decomposition

2018 ◽  
pp. 13-33 ◽  
Author(s):  
Rajeev Sharma ◽  
Ram Bilas Pachori
Keyword(s):  
Empirical Mode Decomposition ◽  
Support Vector ◽  
Automated Classification ◽  
Intrinsic Mode Functions ◽  
Eeg Signals ◽  
Mode Decomposition ◽  
Electroencephalogram Eeg ◽  
Aided Diagnosis ◽  
Bivariate Empirical Mode Decomposition

The chapter presents a new approach of computer aided diagnosis of focal electroencephalogram (EEG) signals by applying bivariate empirical mode decomposition (BEMD). Firstly, the focal and non-focal EEG signals are decomposed using the BEMD, which results in intrinsic mode functions (IMFs) corresponding to each signal. Secondly, bivariate bandwidths namely, amplitude bandwidth, precession bandwidth, and deformation bandwidth are computed for each obtained IMF. Interquartile range (IQR) values of bivariate bandwidths of IMFs are employed as the features for classification. In order to perform classification least squares support vector machine (LS-SVM) is used. The results of the experiment suggest that the computed bivariate bandwidths are significantly useful to discriminate focal EEG signals. The resultant classification accuracy obtained using proposed methodology, applied on the Bern-Barcelona EEG database, is 84.01%. The obtained results are encouraging and the proposed methodology can be helpful for identification of epileptogenic focus.

scholarly journals Bivariate Empirical Mode Decomposition

2007 ◽  
Vol 14 (12) ◽  
pp. 936-939 ◽  
Author(s):  
Gabriel Rilling ◽  
Patrick Flandrin ◽  
Paulo Goncalves ◽  
Jonathan M. Lilly
Keyword(s):  
Empirical Mode Decomposition ◽  
Mode Decomposition ◽  
Bivariate Empirical Mode Decomposition
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