Application of Adaptive Neuro-Fuzzy Logic Method of Noised Electrical Signals for Correction - Can, Erol (TECCIENCIA, 2020)
In this article, the correction of the distorted electrical signal with an adaptive neural fuzzy logic (ANFIS) is discussed due to noise forming at the electrical signal. A sinusoidal signal is widely used both in load supply and in modulation techniques for control and information transport. While the deterioration in a structure of the sinusoidal signal causes energy losses on the power system, it also causes damage to the control signals in the circuit and information transmission signals in telecommunication. Therefore, after considering the structure of the pure reference signal equation, a noise that can occur in the sine structure is included in the reference signal structure. So, an interference signal is formed with the unknown nonlinear process from another noise source for creating the information signal because of an interference signal needs. After an interference signal is generated, the measuring signal is given in the sum of the pure reference signal and the interference signal. For the correction stage of the signals, at inputs of the adaptive fuzzy logic system in the Matlab toolbox, the source signal with noise and the measuring signal values are entered. Then, the experiment is performed via a 3-triangular membership function. When the results are observed, it is seen that the signal which is distorted after the correction operations is very close to the reference signal.