Application of Adaptive Neuro Fuzzy Logic Method of Noised Electrical Signals for Correction

• Can, Erol ^[1]
  1. [1] ERZİNCAN ÜNİVERSTY
• Localización: TECCIENCIA, ISSN-e 2422-3670, ISSN 1909-3667, Vol. 15, Nº. 28, 2020, págs. 1-14
• Idioma: inglés
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• Resumen

  • In this article,    the correction of the distorted electrical signal with an adaptive neural fuzzy logic (ANFIS) due to noise forming in  is discussed. An electrical signal, such as a sinus signal, is widely used both in load supply and in modulation techniques for control and information transport. While the deterioration in the sinus structure causes energy losses, it also causes damage to the control and information transmission signals. Therefore, after considering the structure of the clear reference signal equation, a noise that may occur in the sinus structure is included in the clear reference signal structure. An interference signal must be formed with the unknown nonlinear process from another noise source for measuring of 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. For the correction phase 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 and the experiment is performed via a 3-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