Various Recursive Mixed L2-Linfty Algorithms for Linear-in-the-Parameters Models

In this paper, various Recursive Mixed L2-Linfty (RML) learning algorithms are developed by choosing different forgetting factor matrix function () for Linear-inthe-Parameters (LIP) models, including Projection, Recursive Mixed L2-Linfty, Recursive Mixed Mean L2-Linfty, weighted Mixed L2-Linfty, instantaneous RML, and Batch RML algorithms. A few models are given to apply the proposed RML algorithms for system identification, and some simulations are carried out to show the algorithms’ efficiency and effectiveness.