Rifat Edizkan

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The significance of detection and classification of power quality (PQ) events that disturbs the voltage and/ or current waveforms in the electrical power distribution networks is well known. Consequently, in spite of a large number of research reports in this area, the problem of PQ event classification remains to be an important engineering problem.(More)
In this paper, a novel handwritten digit recognition system is proposed. The system consist of feature extraction, feature selection and classification stages. The features of digits are extracted by using the moment-based and structural-based methods. For the moment-based method, wavelet-based two-dimensional scaling moments (2-DSMs), which have uniquely(More)
In this paper, we propose a new supervised learning method for adaptive neuro-fuzzy inference system (ANFIS) training, which uses the expectation maximiza-tion (EM) algorithm and extended Kalman smoother (EKS) together; we refer to it here as the EM-EKS training method. While the EKS tunes the ANFIS parameters, the EM algorithm estimates the parameters of(More)
Speech recognition is one of the fast moving research areas in pervasive services requiring human interaction. Like any type of pattern recognition system, selection of the feature extraction method and the classifier play a crucial role for speech recognition in terms of accuracy and speed. In this paper, an efficient wavelet based feature extraction(More)