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Toplam kayıt 13, listelenen: 1-10
Hilbert-Huang Transform Based Hierarchical Clustering For Eeg Denoising
(IEEE, 2013)
Empirical mode decomposition (EMD) is a recently introduced decomposition method for non-stationary time series. The sum of the decomposed intrinsic mode functions (IMF) can be used to reconstruct the original signal. ...
Evaluation of bagging ensemble method with time-domain feature extraction for diagnosing of arrhythmia beats
(Springer London Ltd, 2014)
We explore the effect of using bagged decision tree (BDT) as an ensemble learning method with proposed time-domain feature extraction methods on electrocardiogram (ECG) arrhythmia beat classification comparing with single ...
Detrended Fluctuation Analysis For Empirical Mode Decomposition Based Denoising
(IEEE, 2014)
Empirical mode decomposition (EMD) is a recently proposed method to analyze non-linear and non-stationary time series by decomposing them into intrinsic mode functions (IMFs). One of the most popular application of such a ...
Time-frequency methodologies in neurosciences
(Elsevier Inc., 2016)
[No abstract available]
An improved hybrid feature reduction for increased breast cancer diagnostic performance
(Springer Verlag, 2014)
Methods: A hybrid method is proposed using the independent component analysis (ICA) and the discrete wavelet transform (DWT) to reduce feature vectors of Wisconsin diagnostic breast cancer (WDBC) data set. Two independent ...
ECG feature extraction based on the bandwidth properties of variational mode decomposition
(Iop Publishing Ltd, 2016)
It is a difficult process to detect abnormal heart beats, known as arrhythmia, in long-term ECG recording. Thus, computer-aided diagnosis systems have become a supportive tool for helping physicians improve the diagnostic ...
Detrended fluctuation thresholding for empirical mode decomposition based denoising
(Academic Press Inc Elsevier Science, 2014)
Signal decompositions such as wavelet and Gabor transforms have successfully been applied in denoising problems. Empirical mode decomposition (EMD) is a recently proposed method to analyze non-linear and non-stationary ...
Breast Cancer Classification by Using Support Vector Machines with Reduced Dimension
(Croatian Society Electronics Marine, 2011)
Correct and timely diagnosis of diseases is an essential matter in medical field. Limited human capability and limitations decrease the rate of correct diagnosis. Machine learning algorithms such as support vector machine ...
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 ...