Performance and convergence analysis of LMS algorithm

Rapid advances in the field of signal processing are revolutionizing algorithms. This paper describes the concept of adaptive noise cancellation, an alternative method of estimating signals corrupted by additive noise or interference. The Adaptive algorithms are used to improve the convergence rate, signal to noise ratio, stability, mean square error, steady state behavior, tracking, misadjustment has become a focus on digital signal processing. Accurate cancellation of noise in signal processing is a key step of adaptive filter algorithms. In this paper, Acoustic echo cancellation problem was discussed out of different noise cancellation techniques by concerning different parameters with their comparative results. The results shown are using some specific algorithms. The results show, improving convergence rate with less no of taps is the most difficult phase in signal processing applications for the perfect working of any system.