A Novel LMS Algorithm Applied to Adaptive Noise Cancellation with Varying Parameters
Deepanjali Jain
Abstract
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Deepanjali Jain
Abstract
Open-access reader
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.
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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.
Key concepts: Least mean squares filter, Active noise control, Adaptive filter, Computer science, MATLAB, Noise (video), Algorithm, Stability (learning theory)