The aim of this paper is to extend our previous work on a novel and recent class of nonlinear filters called Spline Adaptive Filters (SAFs), implementing the linear part of the Wiener architecture with an IIR filter instead of an FIR one. The new learning algorithm is derived by an LMS approach and a bound on the choice of the learning rate is also proposed. Some experimental results show the effectiveness of the proposed idea.
Nonlinear system identification using IIR spline adaptive filters / Scarpiniti, Michele; Comminiello, Danilo; Parisi, Raffaele; Uncini, Aurelio. - In: SIGNAL PROCESSING. - ISSN 0165-1684. - 108:(2015), pp. 30-35. [10.1016/j.sigpro.2014.08.045]
Nonlinear system identification using IIR spline adaptive filters
SCARPINITI, MICHELE;COMMINIELLO, DANILO;PARISI, Raffaele;UNCINI, Aurelio
2015
Abstract
The aim of this paper is to extend our previous work on a novel and recent class of nonlinear filters called Spline Adaptive Filters (SAFs), implementing the linear part of the Wiener architecture with an IIR filter instead of an FIR one. The new learning algorithm is derived by an LMS approach and a bound on the choice of the learning rate is also proposed. Some experimental results show the effectiveness of the proposed idea.| File | Dimensione | Formato | |
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