An unique adaptive noise canceller with advanced variable-step BLMS algorithm

In recent times noise cancellation is a vital issue, as it is responsible for reducing undesired disturbances in the process of communication. Active Noise Cancellation (ANC) is the most effective technique to cancel noise. ANC has been an active area of research and various adaptive methodologies have been employed to achieve a better ANC scheme. In the ANC technique, the aim is to minimize the noise interference that corrupts the original signal. ANC has a broad variety of applications in common commercial products, industrial uses and other machinery. An analysis of the prevailing adaptive methodologies is necessary for future research as we need to know the demerits of all the prevailing adaptive methodologies in ANC. This paper provides an analysis of various adaptive algorithms for noise cancellation and a comparison is made between them. The strengths, weaknesses and practical effectiveness of all the algorithms have been discussed. This paper deals with cancellation of noise on speech signal using three existing algorithms- Least Mean Square (LMS) algorithm, Normalized Least Mean Square (NLMS) algorithm and Recursive Least Square (RLS) algorithm and a proposed algorithm- advanced Block Least Mean Square (BLMS) algorithm. The algorithms are simulated in MATLAB platform and a tabular comparison of the algorithms is drawn. Finally, conclusions have been drawn by choosing the algorithms that provide efficient performance with less computational complexity.