Yazar "Yildirim, Selcuk" seçeneğine göre listele

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    1D-local binary pattern based feature extraction for classification of epileptic EEG signals
    (Elsevier Science Inc, 2014) Kaya, Yilmaz; Uyar, Murat; Tekin, Ramazan; Yildirim, Selcuk
    In this paper, an effective approach for the feature extraction of raw Electroencephalogram (EEG) signals by means of one-dimensional local binary pattern (1D-LBP) was presented. For the importance of making the right decision, the proposed method was performed to be able to get better features of the EEG signals. The proposed method was consisted of two stages: feature extraction by 1D-LBP and classification by classifier algorithms with features extracted. On the classification stage, the several machine learning methods were employed to uniform and non-uniform 1D-LBP features. The proposed method was also compared with other existing techniques in the literature to find out benchmark for an epileptic data set. The implementation results showed that the proposed technique could acquire high accuracy in classification of epileptic EEG signals. Also, the present paper is an attempt to develop a general-purpose feature extraction scheme, which can be utilized to extract features from different categories of EEG signals. (C) 2014 Elsevier Inc. All rights reserved.
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    A PATTERN RECOGNITION APPROACH FOR CLASSIFICATION OF POWER QUALITY DISTURBANCE TYPES
    (Gazi Univ, Fac Engineering Architecture, 2011) Uyar, Murat; Yildirim, Selcuk; Gencoglu, Muhsin Tunay
    In this study, an algorithm based on pattern recognition approach is proposed for classification of power quality disturbance types. For feature extraction which is an important part of the pattern recognition, a method based on entropy which uses the decomposition coefficients of wavelet transform is presented. The most important advantage of the method is the reduction of data size without losing main distinguishing characteristics of signal. Support vector machines based on statistical learning theory is used as a classifier. The performance of the proposed algorithm is evaluated by using real and synthetic power quality disturbance data. Real power quality disturbance data are obtained from our national power system. Besides, the synthetic power quality disturbance data are obtained from ATP/EMTP and mathematical models. The analyses and results obtained in this study show that proposed algorithm has an efficient, feasible and practical structure.
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    Application of extreme learning machine for estimating solar radiation from satellite data
    (Wiley-Blackwell, 2014) Sahin, Mehmet; Kaya, Yilmaz; Uyar, Murat; Yildirim, Selcuk
    In this paper, a simple and fast method based on extreme learning machine (ELM) for the estimation of solar radiation in Turkey was presented. To design the ELM model, satellite data of the National Oceanic and Atmospheric Administration advanced very high-resolution radiometer from 20 locations spread over Turkey were used. The satellite-based land surface temperature, altitude, latitude, longitude, month, and city were applied as input to the ELM, and the output variable is the solar radiation. To show the applicability of the ELM model, a performance comparison in terms of the estimation capability and the learning speed was made between the ELM model and conventional artificial neural network (ANN) model with backpropagation. The comparison results showed that the ELM model gave better estimation than the ANN model for the overall test locations. Moreover, the ELM model was about 23.5 times faster than the ANN model. The method could be used by researchers or scientists to design high-efficiency solar devices such as solar power plant and photovoltaic cell. Copyright (c) 2013 John Wiley & Sons, Ltd.
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    Design and simulation of active direct current filter for high voltage direct current transmission systems
    (Gazi Univ, Fac Engineering Architecture, 2016) Akdemir, Murat; Yildirim, Selcuk; Genc, Naci
    In this paper, firstly, a monopolar High Voltage Direct Current (HVDC) transmission system model has been formed. Series, parallel and series-parallel active direct current filter designs were carried out to suppress harmonics caused by the converters in this HVDC transmission system. Simulations of the designed HVDC transmission system using these filter were carried out in MATLAB Simulink. Waveforms and total harmonic distortion (THD) values of load current and voltage were obtained in this transmission system model for filtered and unfiltered conditions. Harmonics in the load voltage and current were suppressed to a large extent by active direct current filter used in the HVDC transmission system. Furthermore, THD values for current and voltage were obtained significantly below 5%. According to these results, designed active direct current filters which have simple structure and not complex controller offer significant advantages.