Published Paper Details:

In practical , the characteristics of signal and noise are unknown so that we hardly design a coefficient digital filter. An adaptive filter is a special category of filter that automatically changes its parameters in harmony with input signal by keeping error into account, using some optimizing algorithms. Adaptive filters find applications in various fields such as, noise and echo cancellation, system identification, channel equalization, adaptive inverse system configuration and adaptive linear prediction and so on. This research employment is based on the implementation of adaptive filtering algorithms for noise and echo cancellation Least Mean Square (LMS), Normalized Least Mean Square( NLMS), Recursive Least Square (RLS) algorithms. MATLAB is used as a Software tool. In allusion to this problem, the theory of the adaptive filter and adaptive noise cancellation are researched deeply. The Recursive Least Squares (RLS) algorithms are used in noise cancelling, comparing and analysing the result. It gradually adjusts the error functions and increases the speed of convergence. Compared to most of its competitors, RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity. This has been observed by simulation results