The paper introduces a novel class of complex nonlinear filters, the complex functional link polynomial (CFLiP) filters. These filters present many interesting properties. They are a sub-class of linear-in-the-parameter nonlinear filters. They satisfy all the conditions of Stone-Weirstrass theorem and thus are universal approximators for causal, time-invariant, discrete-time, finite-memory, complex, continuous systems defined on a compact domain. The CFLiP basis functions separate the magnitude and phase of the input signal. Moreover, CFLiP filters include many families of nonlinear filters with orthogonal basis functions. It is shown in the experimental results that they are capable of modeling the nonlinearities of high power amplifiers of telecommunication systems with better accuracy than most of the filters currently used for this purpose.

Introducing complex functional link polynomial filters / Carini, A; Comminiello, D. - STAMPA. - (2017), pp. 4656-4660. (Intervento presentato al convegno IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017) tenutosi a New Orleans, LA nel March 5 - 9, 2017) [10.1109/ICASSP.2017.7953039].

Introducing complex functional link polynomial filters

Comminiello, D
2017

Abstract

The paper introduces a novel class of complex nonlinear filters, the complex functional link polynomial (CFLiP) filters. These filters present many interesting properties. They are a sub-class of linear-in-the-parameter nonlinear filters. They satisfy all the conditions of Stone-Weirstrass theorem and thus are universal approximators for causal, time-invariant, discrete-time, finite-memory, complex, continuous systems defined on a compact domain. The CFLiP basis functions separate the magnitude and phase of the input signal. Moreover, CFLiP filters include many families of nonlinear filters with orthogonal basis functions. It is shown in the experimental results that they are capable of modeling the nonlinearities of high power amplifiers of telecommunication systems with better accuracy than most of the filters currently used for this purpose.
2017
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017)
Nonlinear signal processing; nonlinear filters; complex nonlinear filters; functional link polynomial filters
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Introducing complex functional link polynomial filters / Carini, A; Comminiello, D. - STAMPA. - (2017), pp. 4656-4660. (Intervento presentato al convegno IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017) tenutosi a New Orleans, LA nel March 5 - 9, 2017) [10.1109/ICASSP.2017.7953039].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1100274
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