Performance Analysis of Adaptive filter Algorithms on Different Noise Sources

Noise has become a significant concern in every domain. For instance, in image processing, we can see background noise when we take a snap, also in the field of communication, the information is corrupted by the noises present in the environment, and at the time of decryption, it is becoming challenging. Back then, in earlier days, discrete filters that had fixed frequency response were used to minimize the level of Noise in the information signals. But these filters were not effective as most noise sources have a flat wideband spectrum. After the availability of digital signal processors, to obliterate the wideband Noise, adaptive filters are frequently used in communication systems and digital signal processing systems to filter noisy signals. The Adaptive Noise Cancellation (ANC) approach helps to eliminate the Noise by altering its transient parameters dependent on the incoming signal. In this article, the performance of LMS, NLMS and RLS algorithms is studied for various types of ambient noises. A speech signal that is corrupted by engine noise, waterfall noise, and audio noise and with echo are applied to an ANC filter and the improvement in signal to noise ratio is evaluated with different adaptive filter algorithms.