title: Improving nonlinear modeling capabilities of functional link adaptive filters.
abstract: The functional link adaptive filter (FLAF) represents an effective solution for online nonlinear modeling problems. In this paper, we take into account a FLAF-based architecture, which separates the adaptation of linear and nonlinear elements, and we focus on the nonlinear branch to improve the modeling performance. In particular, we propose a new model that involves an adaptive combination of filters downstream of the nonlinear expansion. Such combination leads to a cooperative behavior of the whole architecture, thus yielding a performance improvement, particularly in the presence of strong nonlinearities. An advanced architecture is also proposed involving the adaptive combination of multiple filters on the nonlinear branch. The proposed models are assessed in different nonlinear modeling problems, in which their effectiveness and capabilities are shown.
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications (DIET), "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy. Electronic address: danilo.comminiello@uniroma1.it.
authors.forename: Danilo
authors.initials: D
authors.lastname: Comminiello
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications (DIET), "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
authors.forename: Michele
authors.initials: M
authors.lastname: Scarpiniti
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications (DIET), "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
authors.forename: Simone
authors.initials: S
authors.lastname: Scardapane
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications (DIET), "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
authors.forename: Raffaele
authors.initials: R
authors.lastname: Parisi
authors.affiliation: Department of Information Engineering, Electronics and Telecommunications (DIET), "Sapienza" University of Rome, Via Eudossiana 18, 00184 Rome, Italy.
authors.forename: Aurelio
authors.initials: A
authors.lastname: Uncini
mesh_terms: D000465:Algorithms; D006801:Humans; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics
keywords: Adaptive combination of filters; Functional links; Nonlinear modeling; Online learning algorithms