Transient Performance Analysis of the ℓ1-RLS

Wei Gao, Jie Chen, Cedric Richard, Shi Wentao, Qunfei Zhang

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The recursive least-squares algorithm with ℓ1-norm regularization (ℓ1-RLS) exhibits excellent performance in terms of convergence rate and steady-state error in identification of sparse systems. Nevertheless few works have studied its stochastic behavior, in particular its transient performance. In this letter, we derive analytical models of the transient behavior of the ℓ1-RLS in the mean and mean-square error sense. Simulation results illustrate the accuracy of these models.

Original languageEnglish
Pages (from-to)90-94
Number of pages5
JournalIEEE Signal Processing Letters
Volume29
DOIs
StatePublished - 2022

Keywords

  • online identification
  • sparse system
  • Transient analysis
  • ℓ-RLS

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