Yazar "Cinar S." seçeneğine göre listele

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    Automatic removal of ocular artefacts in EEG signal by using independent component analysis and artificial neural network
    (Institute of Electrical and Electronics Engineers Inc., 2017) Cinar S.; Menguc E.C.; Acir N.
    Ocular artefacts caused by eye movements can distort Electroencephalogram (EEG) recordings. It is important to obtain clean EEG signals in diagnosing and interpreting diseases. Meaningful EEG signals should not be distorted during the removal of artefacts. In this study, Independent Component Analysis and Artificial Neural Network were used together to remove ocular artefacts. The method was tested by using the real dataset. The Relative Error (RE) and Correlation Coefficient (CC) was used to test the performance of the method. Relative error = 0.227±0.229 and correlation coefficient = 0.941 ±0.088 was calculated in the performance analysis. According to the results, the proposed method is successful in removing ocular artefacts in EEG signals. © 2017 IEEE.
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    Automatic removal of ocular artefacts in EEG signal by using independent component analysis and Chauvenet criterion [Baglmslz bileşen analizi ve chauvenet kriteri kullanarak EEG sinyallerindeki oktiler artefaktlan otomatik yok etme]
    (Institute of Electrical and Electronics Engineers Inc., 2017) Cinar S.; Acir N.
    Eye movements (saccade, blink and etc.) cause artefacts in Electroencephalogram recordings. The ocular artefact can distort the EEG signals. Removal of ocular artefact is important issue in EEG signal analysis. The main task of artefact removal algorithms is to obtain cleaned EEG without losing meaningful EEG signal. The main focus of this work is to remove ocular artefact automatically by using Independent Component Analysis and Chauvenet criterion. The method is tested on real dataset. Relative error and Correlation coefficient are used for the performance test. The performance of the proposed method was Relative error= 0.273±0.148, Correlation coefficients 0.943± 0.042 in the dataset. The results show that the porposed method effectively removes ocular artefacts in EEG. © 2016 IEEE.
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    Comparison of split complex-valued metaheuristic optimization algorithms for system identification problem [Sistem tanimlama problemi için bölünmüş kompleks-degerli sezgisel eniyileme algoritmalarinin karşilaştirilmasi]
    (Institute of Electrical and Electronics Engineers Inc., 2018) Menguc E.C.; Peker M.; Cinar S.
    Since some of the real world problems include phase and amplitude information, complex modeling is more suitable. In this study, the well-used particle swarm optimization, simulated annealing and genetic algorithm are designed in a split form in order to process complex-valued signals. The performances of the algorithms are comparatively tested on two different system identification problems for different noise levels. Simulation results show that the split complex-valued metaheuristic algorithms produce results which are almost close to the weights of both unknown systems. © 2018 IEEE.
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    Quality characteristics of the mixtures of some warm season perennial grasses with alfalfa (Medicago sativa L.) under irrigated conditions in the mediterranean region of Turkey
    (Corvinus University of Budapest, 2018) Cinar S.; Hatipoglu R.; Avci M.; Gundel F.D.; Aktas A.
    This study was conducted to determine forage quality characteristics of duo (alfalfa + one grass) and trio (alfalfa + two grasses) mixtures of some warm season perennial grass species such as dallis grass (Paspalum dilatatum Poir.), Rhodes grass (Chloris gayana L.), Bermuda grass (Cynodon dactylon (L.) Pers.) Guineae grass (Panicum maximum Jacq.), blue couch grass (Digitaria didactyla Willd) and finger grass (Digitaria milanjiana (Rendle) Stapf) with alfalfa as well as their pure sowings under irrigated conditions in the Mediterranean region of Turkey during 2010-2012 growing seasons. In the study, crude protein contents, crude protein yields, acid detergent fiber contents (ADF), neutral detergent fiber contents (NDF), digestible dry matter contents (DDM) and relative feed values (RFV) of the mixtures and pure sowings were determined. The experimental design was completely randomized block design with three replications. The results of the study showed that there were significant differences among mixtures and pure sowings in the forage quality characteristics. The highest crude protein yield (3948.5) kg ha-1) was obtained from the mixture of dallis grass + alfalfa. The highest crude protein ratio (20.5%), DDM ratio (68.3%) and RFV (170.88) was obtained from the pure alfalfa. The highest ADF (40.2%) and NDF (70.9%) was obtained from the pure Guinea grass. From the results of the study, it was concluded that Bermuda grass, Rhodes grass, blue couch grass and dallis grass could be used to establish of duo and trio pasture mixtures with alfalfa, having long grazing season and giving high hay quality. Before the establishment of such pasture mixtures, it is needed to search for proper mixture ratios and proper management techniques of the mixtures. © 2018, ALÖKI Kft., Budapest, Hungary.