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Sparsity-aware distributed adaptive filtering with robustness against impulsive noise and low SNR

Author

Listed:
  • Rafael Moura Carmo

    (CEFET-RJ)

  • Guilherme R. Ferreira

    (CEFET-RJ)

  • Pedro Henrique Campelo

    (CEFET-RJ)

  • Leonardo C. Resende

    (IFRJ)

  • Leonardo Lima

    (CEFET-RJ)

  • Felipe Rocha Henriques

    (CEFET-RJ)

  • Diego Barreto Haddad

    (CEFET-RJ)

Abstract

Distributed inference tasks could be performed by adaptive filtering techniques. Several enhancement strategies for such techniques were proposed, such as sparsity-aware algorithms, coefficients reuse and correntropy-based cost functions in the case of impulsive noise. In this paper, a general framework based on Lagrange multipliers for the derivation of sophisticated algorithms that incorporate most of these improvements is described. A new general identification algorithm is derived as an example of the proposed approach and its performance is assessed in a distributed setting.

Suggested Citation

  • Rafael Moura Carmo & Guilherme R. Ferreira & Pedro Henrique Campelo & Leonardo C. Resende & Leonardo Lima & Felipe Rocha Henriques & Diego Barreto Haddad, 2024. "Sparsity-aware distributed adaptive filtering with robustness against impulsive noise and low SNR," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 86(3), pages 451-461, July.
    • Handle: RePEc:spr:telsys:v:86:y:2024:i:3:d:10.1007_s11235-024-01124-7
    DOI: 10.1007/s11235-024-01124-7
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