Abstract
This paper presents adaptive Noise Cancelation (ANC) by Normalized Least Mean Square (NLMS) algorithm and also showcases its efficiency over other algorithms like Recursive Least Square (RLS) algorithm and the Least Mean Squares (LMS). In this paper, we have improved and also optimized the step size value (µ) which determines the convergence in the mean. Improper value can cause sharp changes in variance which will be misleading and is one of the major problems of least mean squares algorithm. The aim of this paper is to highlight and statistically compare the algorithms and also demonstrate the effectiveness of normalized least mean square algorithms with various additive noises.
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