Antiderivative Antialiasing for Memoryless Nonlinearities

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2017-07
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Mcode
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Language
en
Pages
5
1049-1053
Series
IEEE SIGNAL PROCESSING LETTERS, Volume 24, issue 7
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.
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Keywords
Aliasing, harmonic distortion, nonlinear systems, signal denoising, signal processing algorithms, WAVE-FORMS, OSCILLATOR, DISTORTION, SIGNALS, FILTER
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Citation
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