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Transient Performance Analysis of the L1-RLS

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 sense. Simulation results illustrate the accuracy of these models.
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https://hal.archives-ouvertes.fr/hal-03347324
Contributor : Cédric Richard Connect in order to contact the contributor
Submitted on : Friday, September 17, 2021 - 10:27:58 AM
Last modification on : Saturday, September 18, 2021 - 3:34:00 AM

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  • HAL Id : hal-03347324, version 1

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Wei Gao, Jie Chen, Cédric Richard, Wentao Shi, Qunfei Zhang. Transient Performance Analysis of the L1-RLS. 2021. ⟨hal-03347324⟩

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