New variant of NLMS/F algorithm with low computational cost

Authors

  • Laura Jazmín Hidalgo Hernández Instituto Politécnico Nacional
  • Ángel Alfonso Vázquez Piña Instituto Politécnico Nacional
  • Xochitl Maya Rosales Instituto Politécnico Nacional
  • Juan Gerardo Avalos Ochoa Instituto Politécnico Nacional https://orcid.org/0000-0001-8516-2524
  • Giovanny Sánchez Rivera Instituto Politécnico Nacional

DOI:

https://doi.org/10.37537/rev.elektron.6.2.163.2022

Keywords:

NLMF algorithm, NLMS/F algorithm, set membership, adaptive filtering

Abstract

Adaptive filters are used in a wide variety of signal processing applications (e.g., acoustic echo cancellation, system identification, channel equalization, etc.). Adaptive algorithms are an essential part of adaptive filters since they update the filter coefficients to model the desired response. Therefore, adaptive algorithms must have low computational cost and high speed of convergence. In this paper, a new variant of the Normalized Least-Mean-Fourth (NLMF) algorithm based on set membership is presented, in addition, a method to automatically adjust the step size is presented. To evaluate its performance, the algorithm was simulated in system identification and acoustic echo cancellation applications. The results demonstrate that the proposed algorithm improves the convergence speed and exhibits low computational cost compared to the conventional NLMS/F algorithm.

Downloads

Download data is not yet available.

References

S. S. Haykin, Adaptive filter theory, Fifth edition, International edition. Upper Saddle River Boston Columbus San Francisco New York: Pearson, 2014.

S. Li, S. Wu, Y. Wang, W. Guo, y Y. Zhou, "An improved NLMS algorithm based on speech enhancement", en 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, China, dic. 2015, pp. 896-899. doi: 10.1109/IAEAC.2015.7428686.

F. Wang, Q. Wang, F. Liu, J. Chen, L. Fu, y F. Zhao, "Improved NLMS-based adaptive denoising method for ECG signals", THC, vol. 29, n.º 2, pp. 305-316, mar. 2021, doi: 10.3233/THC-202659.

J. Benesty, C. Paleologu, S. Ciochina, E. V. Kuhn, K. J. Bakri, y R. Seara, "LMS and NLMS Algorithms for the Identification of Impulse Responses with Intrinsic Symmetric or Antisymmetric Properties", en ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, Singapore, may 2022, pp. 5662-5666. doi: 10.1109/ICASSP43922.2022.9747430.

A. Zerguine, "Convergence and steady-state analysis of the normalized least mean fourth algorithm", Digital Signal Processing, vol. 17, n.º 1, pp. 17-31, ene. 2007, doi: 10.1016/j.dsp.2006.01.005.

E. Eweda y N. J. Bershad, "Stochastic Analysis of a Stable Normalized Least Mean Fourth Algorithm for Adaptive Noise Canceling With a White Gaussian Reference", IEEE Trans. Signal Process., vol. 60, n.º 12, pp. 6235-6244, dic. 2012, doi: 10.1109/TSP.2012.2215607.

A. Zerguine, "Convergence behavior of the normalized least mean fourth algorithm", en Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154), Pacific Grove, CA, USA, 2000, vol. 1, pp. 275-278. doi: 10.1109/ACSSC.2000.910958.

B. Mohanty, H. K. Sahoo, y B. Patnaik, "Block NLMS/F-based equalizer design and channel capacity analysis for indoor IEEE 802.11 fading wireless channels", SIViP, vol. 13, n.º 4, pp. 693-701, jun. 2019, doi: 10.1007/s11760-018-1398-2.

B. Mohanty, H. K. Sahoo, y B. Patnaik, "NLMS/F Based Adaptive Beam former for Indoor Wireless Channel", en 2017 Ninth International Conference on Advanced Computing (ICoAC), Chennai, dic. 2017, pp. 87-91. doi: 10.1109/ICoAC.2017.8441186.

P. S. R. Diniz, "Set-Membership Adaptive Filtering", en Adaptive Filtering: Algorithms and Practical Implementation, P. S. R. Diniz, Ed. Cham: Springer International Publishing, 2020, pp. 189-229. doi: 10.1007/978-3-030-29057-3_6.

I. Hassani, M. Arezki, y A. Benallal, "A novel set membership fast NLMS algorithm for acoustic echo cancellation", Applied Acoustics, vol. 163, p. 107210, jun. 2020, doi: 10.1016/j.apacoust.2020.107210.

S. Gollamudi, S. Nagaraj, S. Kapoor and Yih-Fang Huang, "Set-membership filtering and a set-membership normalized LMS algorithm with an adaptive step size," in IEEE Signal Processing Letters, vol. 5, no. 5, pp. 111-114, May 1998, doi: 10.1109/97.668945.

C. Paleologu, S. Ciochina and J. Benesty, "Variable Step-Size NLMS Algorithm for Under-Modeling Acoustic Echo Cancellation," in IEEE Signal Processing Letters, vol. 15, pp. 5-8, 2008, doi: 10.1109/LSP.2007.910276.

Downloads

Published

2022-12-15

Issue

Vol. 6 No. 2 (2022)

Section

Signal Processing

License

The authors who publish in this journal agree with terms established in the license Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

How to Cite

[1]
L. J. Hidalgo Hernández, Ángel A. Vázquez Piña, X. Maya Rosales, J. G. Avalos Ochoa, and G. Sánchez Rivera, “New variant of NLMS/F algorithm with low computational cost”, Elektron, vol. 6, no. 2, pp. 96–100, Dec. 2022, doi: 10.37537/rev.elektron.6.2.163.2022.