Aliasing Reduction in Virtual Analogue Modelling

Abstract: Aliasing is an inherent problem in virtual analogue modelling when simulating nonlinear systems such as guitar amplifiers and distortion effects units. Such systems introduce harmonics into the signal, which in the discrete-time domain can exceed the Nyquist frequency, resulting in unpleasant aliasing distortion. Recent research has shown that aliasing can be significantly reduced by using the antiderivatives of the nonlinear function, and that this method can be applied to systems with state as well as memoryless nonlinearities. In this work, the application of antiderivative antialiasing in the state-space modelling of several nonlinear circuits will be outlined in detail. Existing literature has focused on one-port nonlinearities, so in this work a method for two-port nonlinearities is proposed and demonstrated by example. Furthermore, a second order antialiasing method for state-space models is presented. The antialiasing methods were found to significantly improve the signal to noise ratio and reduce aliasing at low oversampling rates. In the case of scalar nonlinearities, the methods introduced no notable extra computational cost, but for two-port nonlinearities the processing time increased with the order of antialiasing. Finally, the suitability of antiderivative antialiasing in a real-time context was demonstrated through the development of a virtual analogue guitar effects plug-in.

Recommended citation: A. Carson, “Aliasing Reduction in Virtual Analogue Modelling”, MSc Thesis, University of Edinburgh, 2020
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