Nonlinear waveshaping is a common technique in musical signal processing, both in a static memoryless context and within feedback systems. Such waveshaping is usually applied directly to a sampled signal, generating harmonics that exceed the Nyquist frequency and cause aliasing distortion. This problem is traditionally tackled by oversampling the system. In this paper, we present a novel method for reducing this aliasing by constructing a continuous-time approximation of the discrete-time signal, applying the nonlinearity to it, and filtering in continuous-time using analytically applied convolution. The presented technique markedly reduces aliasing distortion, especially in combination with low order oversampling. The approach is also extended to allow it to be used within a feedback system.

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The article performs a generic comparison of integrator- and differentiator based continuous-time systems as well as their discretetime models, aiming to answer the reoccurring question in the music DSP community of whether there are any benefits in using differentiators instead of conventionally employed integrators. It is found that both kinds of models are practically equivalent, but there are certain reservations about differentiator based models.

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