Adaptive Digital FIR Filters: A Study; Case Study: Noise Cancellation using LMS Algorithm

Abstract

In this paper, a review has been taken to the previous and the most recent studies and investigations on adaptive digital filter algorithms which based on adaptive noise cancellation systems. In numerous applications of noise cancellation such modern and adaptive systems characteristics that could be very quick in changing the situations which needs the utilization of adaptive filters that quickly changes accordingly. Algorithms such as LMS and RLS proves to be crucial within the noise cancellation are looked into counting guideline and later alterations to extend the merging rate and reduce the computational complexity for future execution. This paper, isn't only as a review of the basic principles on which of the adaptive filters are based uses least mean square LMS algorithm derivation of the least-mean-square (LMS) algorithm; but moreover; It's to implement a case-study of the adaptive filters to solve real-world application problems such as adaptive noise cancellation by implementing the LMS finite impulse response (FIR) adaptive filter using MATLAB, then, investigate of how to choose an appropriate value of convergence factor in order to achieve an efficient LMS adaptive filter