Antiderivative Antialiasing for Memoryless Nonlinearities

Stefan Bilbao*, Fabian Esqueda Flores, Julian D. Parker, Vesa Välimäki

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

9 Sitaatiot (Scopus)
165 Lataukset (Pure)

Abstrakti

Aliasing is a commonly encountered problem in audio signal processing, particularly when memoryless nonlinearities are simulated in discrete time. A conventional remedy is to operate at an oversampled rate. A new aliasing reduction method is proposed here for discrete-time memoryless nonlinearities, which is suitable for operation at reduced oversampling rates. The method employs higher order antiderivatives of the nonlinear function used. The first-order form of the new method is equivalent to a technique proposed recently by Parker et al. Higher order extensions offer considerable improvement over the first antiderivative method, in terms of the signal-to-noise ratio. The proposed methods can be implemented with fewer operations than oversampling and are applicable to discrete-time modeling of a wide range of nonlinear analog systems.

AlkuperäiskieliEnglanti
Sivut1049-1053
Sivumäärä5
JulkaisuIEEE Signal Processing Letters
Vuosikerta24
Numero7
DOI - pysyväislinkit
TilaJulkaistu - heinäkuuta 2017
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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