Transient Performance Analysis of the $\ell_1$-RLS
Signal Processing
2022-02-02 v2
Abstract
The recursive least-squares algorithm with -norm regularization (-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 -RLS in the mean and mean-square sense. Simulation results illustrate the accuracy of these models.
Keywords
Cite
@article{arxiv.2109.06749,
title = {Transient Performance Analysis of the $\ell_1$-RLS},
author = {Wei Gao and Jie Chen and Cédric Richard and Wentao Shi and Qunfei Zhang},
journal= {arXiv preprint arXiv:2109.06749},
year = {2022}
}
Comments
5 pages, 2 figures