Adaptive Noise Cancellation Using NLMS Algorithm

  • R. RashmiEmail author
  • Shweta Jagtap
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)


This paper studies the behaviour of normalized least mean square (NLMS) adaptive filter algorithm-based noise canceller to eliminate intense background noise of high and low frequency from a desired signal. Noise signal filtration requires a filter which automatically adapts with the variation of input signal and noise signal. Performance is measured by optimizing rate of convergence and mean square error (MSE) using MATLAB. The experimental results indicate that adaptive noise canceller can remove low- and high-frequency noise of signals conveniently, and for small values of step size MSE decreases and for larger value of step size the rate of convergence increases. The computation time increases with the increase of filter length.


Adaptive filters LMS algorithm NLMS algorithm Active noise control 



This work has been supported by DST-PURSE, Savitribai Phule Pune University. One of the authors R. Rashmi is thankful to the University Grant Commission (UGC) for SRF.


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Instrumentation ScienceSavitribai Phule Pune UniversityPuneIndia

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