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Emulation of Hammerstein nonlinearities using Volterra series is a popular approach for black box modelling of digital and analog nonlinearities. A simplified nonlinear Volterra model (SNVM) is a method of capturing the behaviour of a static nonlinear system. Emulation of the nonlinearity using SNVM on band–limited signals introduces aliasing. Antiderivative antialiasing (ADAA) when applied to band–limited signals is a novel approach of achieving antialiasing for SNVM, however it is computationally intensive to be practical for real time applications. In this paper, we use different optimization strategies to reduce the complexity of the algorithm and achieve faster than real-time black box modelling of static Hammerstein nonlinearities.
Author (s): Arora, Satyarth; Bennett, Christopher
Affiliation:
University of Miami, Coral Gables, FL, USA; University of Miami, Coral Gables, FL, USA
(See document for exact affiliation information.)
AES Convention: 153
Paper Number:10632
Publication Date:
2022-10-06
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Session subject:
Signal Processing
Permalink: https://aes2.org/publications/elibrary-page/?id=21961
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Arora, Satyarth; Bennett, Christopher; 2022; Fast Algorithms for Black Box Modelling of Static Hammerstein Nonlinearities [PDF]; University of Miami, Coral Gables, FL, USA; University of Miami, Coral Gables, FL, USA; Paper 10632; Available from: https://aes2.org/publications/elibrary-page/?id=21961
Arora, Satyarth; Bennett, Christopher; Fast Algorithms for Black Box Modelling of Static Hammerstein Nonlinearities [PDF]; University of Miami, Coral Gables, FL, USA; University of Miami, Coral Gables, FL, USA; Paper 10632; 2022 Available: https://aes2.org/publications/elibrary-page/?id=21961