Uyarlamalı filtre uygulamalarının kullanılması ile gürültünün yok edilmesi

The aim of this research is to study the theoretical adaptive filters for noise canceling problem. Firstly, it describes the notion using adaptive filters. Secondly, it presents three more common adaptive filters the RLS, NLMS and LMS algorithms. In addition, it describes the implementation of adaptive filters. Furthermore, the aim of this study is to solve some of the noise problems that affect the performance of the systems. The use of Noise Canceling theories is the most important solution for this problem, and for that research adaptive filters are used to solve these problems. The most important algorithms for these filters are RLS, NLMS and LMS algorithms. The research tests these algorithms with adaptive filters applications (noise cancellation, signal prediction, system identification, echo cancellation), and have chosen the best algorithm based on the value of Mean Square Error (MSE). The research presents two examples of a solution for the noise problem of the voice signal using Simulink MATLAB for different environments. The first example is active noise canceling theory, where, the color noise and then white noise (Gaussian noise) on the audio signal is used, after that three algorithms RLS, LMS, NLMS are applied to the audio signal to detect and cancel both noises. The second example is Channel Equalization, which also applies the three algorithms to solve the very same problem. Finally, the results of this Simulink are discussed and future work is present.