article · 2003

Relative convergence of the cascade RLS with subsection adaptation algorithm

Cited by 1Abstract and details only

Abstract

We analyze the convergence behavior of the CRLS-SA algorithm for inverse filtering. The CRLS-SA is a cascade adaptive filter based on the RLS algorithm, with each section adapted independently based on global minimization. The subsection adaptation results in reduced computational complexity. The rate of convergence is evaluated based on the convergence time constant defined as the ratio of condition number and sensitivity. The smaller the convergence time constant, the faster the structure converges. Analysis and simulation explain and show that CRLS-SA exhibits faster convergence than the direct form RLS adaptive filter for speech type signals.

Cite this paper

APA 7

Zakaria, G., & Beex, A. (2003). Relative convergence of the cascade RLS with subsection adaptation algorithm. https://doi.org/10.1109/acssc.1999.832441

MLA 9

Zakaria, G., and A.A. Beex. “Relative convergence of the cascade RLS with subsection adaptation algorithm.” vol. 1, 2003, pp. 810–14, https://doi.org/10.1109/acssc.1999.832441.

Chicago

Zakaria, G., and A.A. Beex. 2003. “Relative convergence of the cascade RLS with subsection adaptation algorithm.” https://doi.org/10.1109/acssc.1999.832441.

Harvard

Zakaria, G. and Beex, A. (2003) ‘Relative convergence of the cascade RLS with subsection adaptation algorithm’. Available at: https://doi.org/10.1109/acssc.1999.832441.

BibTeX

@article{zakaria2003relative,
  title = {{Relative convergence of the cascade RLS with subsection adaptation algorithm}},
  author = {Zakaria, G. and Beex, A.A.},
  volume = {1},
  pages = {810--814},
  year = {2003},
  doi = {10.1109/acssc.1999.832441}
}

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