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L2-Stability Analysis of the SM-NLMS Algorithm

Published 11 Jan 2020 in eess.SP | (2001.03616v1)

Abstract: In this letter, we analyze, two properties, the local and the global robustness of the set-membership normalized least mean square (SM-NLMS) algorithm. We will show that the SM-NLMS algorithm has l2-stability. Indeed, the SM-NLMS algorithm never diverges; no matter how the parameters of the SM-NLMS algorithm has been selected. Ultimately, the numerical simulations corroborate the validity of our analysis.

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Authors (1)

  1. Rajab Shabaani 

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