Open AccessA Novel LMS Algorithm Applied to Adaptive Noise Cancellation with Varying Parameters
Author(s) -
Deepanjali Jain
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40179
Subject(s) - least mean squares filter , active noise control , adaptive filter , computer science , matlab , noise (video) , algorithm , stability (learning theory) , control theory (sociology) , filter (signal processing) , convergence (economics) , multidelay block frequency domain adaptive filter , kernel adaptive filter , filter design , artificial intelligence , machine learning , control (management) , economics , image (mathematics) , computer vision , economic growth , operating system
Abstract: Adaptive filters have become active area of research in the field of communication system. This paper explores the novel concept of adaptive noise cancellation (ANC) using least-mean-square (LMS) adaptive filters. The model of the LMS-ANC is designed and simulated in MATLAB environment. The proposed algorithm utilizes adaptive filters to evaluate gradients accurately which results in good adaptation, stability and performance. The objective of this investigation is to provide solution in order to improve the performance of noise canceller in terms of filter parameters. The results are obtained with the help of adaptive algorithm with variable step size and filter order in order to deliver high convergence speed and stability of the error signal. Keywords: Adaptive Noise cancellation, LMS algorithm, MATLAB, Filter order, Step size.