Muhammet Mustafa Çodur

E-mail

mcodur@metu.edu.tr

Department

Graduate School of Natural and Applied Sciences

ORCID

0000-0002-6439-7372

Web of Science Researcher ID

AAZ-5227-2020

EFFECT OF CONTACT RESISTANCE ON SERIES RESISTANCE OF SILVER NANOWIRE TRANSPARENT ELECTRODES Çodur, Muhammet Mustafa; Tsoi, Konstantin; KOÇ, MEHMET; Ünalan, Hüsnü Emrah; Yerci, Selçuk (2022-07-07)
Gender Classification Based on EEG Signal Çodur, Muhammet Mustafa; Özbek, İbrahim Yücel (2017-12-19)
Sleep Stage Classification Based on EEG signal Oral, Emin Argun; Çodur, Muhammet Mustafa; Özbek, İbrahim Yücel (null; 2017-12-19)
Cepstrum coefficients based sleep stage classification Oral, Emin Argun; Çodur, Muhammet Mustafa; Özbek, İbrahim Yücel (null; 2017-12-12) This paper examines filterbank parameters to extract discriminative cepstrum coefficient from EEG signals for sleep stage classification using well-known Support Vector Machine (SVM) algorithm. The proposed method has thre...
Dependence of Modulation Responce on Laser Parameters in Hybrid Lasers Çodur, Muhammet Mustafa; Çakmak, Bülent (null; 2017-12-09)
Sleep stage classification based on filter bank optimization ORAL, EMİN ARGUN; Çodur, Muhammet Mustafa; ÖZBEK, İBRAHİM YÜCEL (2017-12-01) Sleep stage binary classification is studied using single channel EEG signals. The proposed approach is composed of two steps. In the first step, cepstrum coefficients based features are obtained from EEC signals using a f...
Generalized filter bank design for sleep stage classification ORAL, EMİN ARGUN; Çodur, Muhammet Mustafa; ÖZBEK, İBRAHİM YÜCEL (2017-11-02) In this study, binary sleep stage classification (sleep or awake state) was performed using single-channel EEG signal. A new frequency warping function is proposed for this purpose. This function provides a bending functio...
Gender clasification based on single channel EEG signal ORAL, EMİN ARGUN; ÖZBEK, İBRAHİM YÜCEL; Çodur, Muhammet Mustafa (2017-11-02) This paper presents an approach for gender recognition from single channel EEG signal. For this purpose, approximately 24 hour-long EEG data, obtained during daily routine activities including sleep, was used. First, cepst...
Gender Classification Based on EEG Signal Çodur, Muhammet Mustafa; Özbek, İbrahim Yücel (2017-10-16)

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