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This study introduces the concept of decision tree (DT) classification, a new approach to power transformer differential protection. The proposed technique is based on processing the differential current. The suggested method detects winding insulation failures and distinguishes them from magnetising inrush and sympathetic inrush conditions with classification accuracies of 100% for simulations and 95% for real-time studies. The internal faults can be accurately recognised from inrush current conditions in a few sampling cycle after the occurrence of a disturbance. Another advantage of the proposed method is that the fault detection algorithm does not depend on the selection of thresholds. Performance analysis of the DT is achieved by the simulation of different faults and switching conditions on a power transformer in power system computer aided design/electromagnetic transients including DC (PSCAD/EMTDC). Furthermore, the proposed method is also tested in laboratory environment. The accuracy of DT is also compared with support vector machine. Both experimental and simulation results are presented and discussed.

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Mobile communication has become an important part of our daily lives for voice communication, data sharing and access over the Internet. Mobile communication is an open network, so maintaining the privacy and reliability of data has always been anxiety. The reliability of the data against channel noise can be achieved by various error correction codes. The purpose of the channel coding process is to reduce the effect of some disruptive elements that the data is influenced in the transmission phase as much as possible. This procedure ensures that the data is delivered to the receiver with minimum error. In this study, a communication system was established in MATLAB environment for the transmission of five second audio signal. In this communication system, BER and MSE performances of four phase shift keying methods are obtained first. In the second phase of the study, the AWGN and Rician fading channels were individually coded with four different LBC types. Performance evaluation of these coding types was done with BER and MSE criteria. In the last part of the study, it was investigated which wavelet family is suitable for which level, in order to ensure audio transmission over AWGN and Rician fading channels with the least possible error. Four wavelet transform families at different levels were applied to the audio signal for LBC (7, 4), LBC (15, 8), LBC (17, 8) and LBC (23, 12) encoded channels, and the Mean Squared Error (MSE) performances were compared.

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where he is also the Director of the Advanced Robotics Laboratory. He is engaged in teaching and conducting research in signals and systems with emphasis on controls, signal processing, modeling, robotics, and computational intelligence.