Transient Performance Analysis of the L1-RLS
Résumé
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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