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Toplam kayıt 15, listelenen: 11-15
Epilepsy detection using Empirical Mode Decomposition and detrended Fluctuation Analysis
(IEEE, 2015)
In this study, a new method is presented to analyze electroencephalography (EEG) signals by deploying recently proposed adaptive and data driven signal processing method called Empirical Mode Decomposition (EMD). The EMD ...
Analysis of EEG Signals by Emprical Mode Decomposition and Mutual Information
(IEEE, 2013)
Empirical mode decomposition has been recently proposed to analyze non-stationary signals. It decomposes the signal into intrinsic mode functions (IMF) which are derived from the signal itself. However, it is still an ...
Random subspace method with class separability weighting
(Wiley, 2016)
The random subspace method (RSM) is one of the ensemble learning algorithms widely used in pattern classification applications. RSM has the advantages of small error rate and improved noise insensitivity due to ensemble ...
ECG signal analysis based on variational mode decomposition and bandwidth property
(IEEE, 2016)
In this paper, the bandwidth properties of the modes obtained using the variational mode decomposition (VMD) are analyzed to detect arrhythmia electrocardiogram (ECG) beats. The VMD is an enhanced version of the empirical ...
EOG denoising using empirical mode decomposition and detrended fluctuation analysis
(IEEE, 2014)
In this study, a method is presented for the removal of electrooculogram (EOG) noise from electroencephalography (EEG) recordings by using recently proposed data driven approach called Empirical Mode Decomposition (EMD). ...