Yazar "Mert, Ahmet" için listeleme
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Analysis of EEG signals by emprical mode decomposition and mutual information
Mert, Ahmet; Akan, Aydın (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 ... -
Analysis of EEG Signals by Emprical Mode Decomposition and Mutual Information
Mert, Ahmet; Akan, Aydın (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 ... -
Breast Cancer Classification by Using Support Vector Machines with Reduced Dimension
Mert, Ahmet; Kılıç, Niyazi; Akan, Aydın (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 ... -
Breast Cancer Detection with Reduced Feature Set
Mert, Ahmet; Kılıç, Niyazi; Bilgili, Erdem; Akan, Aydın (Hindawi Ltd, 2015)This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature ... -
Detrended Fluctuation Analysis For Empirical Mode Decomposition Based Denoising
Mert, Ahmet; Akan, Aydın (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 ... -
Detrended fluctuation thresholding for empirical mode decomposition based denoising
Mert, Ahmet; Akan, Aydın (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 ... -
ECG feature extraction based on the bandwidth properties of variational mode decomposition
Mert, Ahmet (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 ... -
ECG signal analysis based on variational mode decomposition and bandwidth property
Mert, Ahmet (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 ... -
EEG denoising based on empirical mode decomposition and mutual information
Mert, Ahmet; Akan, Aydın (Springer Verlag, 2014)Empirical mode decomposition (EMD) is a recently introduced decomposition method for non-stationary time series. EMD has an information preserving property so the sum of the decomposed intrinsic mode functions (IMF) can ... -
EOG denoising using empirical mode decomposition and detrended fluctuation analysis
Mert, Ahmet; Akkurt, Nihan; Akan, Aydın (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). ... -
Epilepsy detection using Empirical Mode Decomposition and detrended Fluctuation Analysis
Mert, Ahmet; Akan, Aydın (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 ... -
Evaluation of bagging ensemble method with time-domain feature extraction for diagnosing of arrhythmia beats
Mert, Ahmet; Kılıç, Niyazi; Akan, Aydın (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 ... -
Hilbert-Huang Transform Based Hierarchical Clustering For Eeg Denoising
Mert, Ahmet; Akan, Aydın (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. ... -
An improved hybrid feature reduction for increased breast cancer diagnostic performance
Mert, Ahmet; Kılıç, Niyazi; Akan, Aydın (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 ... -
Random subspace method with class separability weighting
Mert, Ahmet; Kılıç, Niyazi; Bilgili, Erdem (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 ... -
A test and simulation device for Doppler-based fetal heart rate monitoring
Mert, Ahmet; Sezdi, Mana; Akan, Aydın (Tubitak Scientific & Technical Research Council Turkey, 2015)The Doppler effect is the preferred technique in fetal heart rate (FHR) monitoring devices. The main objective of the recent studies on the Doppler FHR has been to improve the accuracy. On the other hand, a reliable fetal ... -
Time-frequency methodologies in neurosciences
Boashash, B.; Stevenson, N.J.; Rankine, L.J.; Stevenson, N.J.; Azemi, G.; Sejdic, E.; Mert, Ahmet (Elsevier Inc., 2016)[No abstract available]
