Antiderivative Antialiasing for Memoryless Nonlinearities
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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5
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IEEE Signal Processing Letters, Volume 24, issue 7, pp. 1049-1053
Abstract
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.Description
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Bilbao, S, Esqueda Flores, F, Parker, J D & Välimäki, V 2017, 'Antiderivative Antialiasing for Memoryless Nonlinearities', IEEE Signal Processing Letters, vol. 24, no. 7, pp. 1049-1053. https://doi.org/10.1109/LSP.2017.2675541