Performance Comparison of LMS and RLS Algorithms for Ambient Noise Attenuation

Authors

  • Amira Chiheb Faculty of Electrical Engineering, University of Sciences and Technology Houari Boumediene, Algeria
  • Hassina Khelladi Faculty of Electrical Engineering, University of Sciences and Technology Houari Boumediene, Algeria

DOI:

https://doi.org/10.53375/ijecer.2024.383

Keywords:

Active noise control, FIR filter, LMS algorithm, RLS algorithm

Abstract

The aim of this study is to implement two different types of adaptive algorithms for the noise cancellation. The study explores the well-known least mean squares (LMS) adaptive algorithm, which is based on stochastic gradient descent approach, and its performances in terms of noise attenuation level and swiftness in active noise control (ANC). Another algorithm is considered in this investigation based upon the use of the least squares estimation (LSE), commonly named, the recursive least squares algorithm (RLS), and will be compared to the LMS. In order to evaluate the potential of each one, a few simulations are achieved. The numerical experiments are performed by using several real recordings of different environment noises tested on the two proposed adaptive algorithms. A comparison is emphasized regarding noise suppression ability and convergence speed, by implementing both adaptive algorithms on the same noise sources. From this numerical study, the RLS algorithm reveals a faster convergence speed and better control performances than the LMS algorithm.

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Published

15.03.2024

How to Cite

Chiheb, A., & Khelladi , H. . (2024). Performance Comparison of LMS and RLS Algorithms for Ambient Noise Attenuation. International Journal of Electrical and Computer Engineering Research, 4(1), 14–19. https://doi.org/10.53375/ijecer.2024.383