In this paper, we show how to expand the class of audio circuits that can be modeled using Wave Digital Filters (WDFs) to those involving operational transconductance amplifiers (OTAs). Two types of behavioral OTA models are presented and both are shown to be compatible with the WDF approach to circuit modeling. As a case study, an envelope filter guitar effect based around OTAs is modeled using WDFs. The modeling results are shown to be accurate when to compared to state of the art circuit simulation methods.

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The voltage-controlled low-pass filter of the Korg MS-50 synthesizer is built around a non-linear diode bridge as the cutoff frequency control element, which greatly contributes to the sound of this vintage synthesizer. In this paper, we introduce the overall filter circuitry and give an in-depth analysis of this diode bridge. It is further shown how to turn the small signal equivalence circuit of the bridge into the necessary two-resistor configuration to uncover the underlying Sallen-Key structure. In a second step, recent advances in the field of WDFs are used to turn a simplified version of the circuit into a virtual-analog model. This model is then examined both in the small-signal linear domain as well as in the non-linear region with inputs of different amplitudes and frequencies to characterize the behavior of such diode bridges as cutoff frequency control elements.

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Previous grouped-nonlinearity formulations for Wave Digital Filter (WDF) modeling of nonlinear audio circuits assumed that nonlinear (NL) devices with memoryless voltage–current characteristics were modeled as voltage-controlled current sources (VCCSs). These formulations cannot accommodate nonlinear devices whose equations cannot be written as NL VCCSs, and they cannot accommodate circuits with cutsets composed entirely of current sources (including NL VCCSs). In this paper we generalize independent and dependent variable choice at the root of WDF trees to accommodate both these cases, and review two graph theorems for avoiding forbidden cutsets and loops in general.

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In this paper a new technique is introduced that allows for the variable step-size simulation of wave digital filters. The technique is based on the preservation of the underlying network variables which prevents fluctuation in the stored energy in reactive network elements when the step-size is changed. This method allows for the step-size variation of wave digital filters discretized with any passive discretization technique and works with both linear and nonlinear reference circuits. The usefulness of the technique with regards to audio circuit simulation is demonstrated via the case study of a relaxation oscillator where it is shown how the variable step-size technique can be used to mitigate frequency error that would otherwise occur with a fixed step-size simulation. Additionally, an example of how aliasing suppression techniques can be combined with physical modeling is given with an example of the polyBLEP antialiasing technique being applied to the output voltage signal of the relaxation oscillator.

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Modal representations—decomposing the resonances of objects into their vibrational modes has historically been a powerful tool for studying and synthesizing the sounds of physical objects, but it also provides a flexible framework for abstract sound synthesis. In this paper, we demonstrate a variety of musically relevant ways to modify the model upon resynthesis employing a carillon model as a case study. Using a set of audio recordings of the sixty bells of the Robert and Ann Lurie Carillon recorded at the University of Michigan, we present a modal analysis of these recordings, in which we decompose the sound of each bell into a sum of decaying sinusoids. Each sinusoid is characterized by a modal frequency, exponential decay rate, and initial complex amplitude. This analysis yields insight into the timbre of each individual bell as well as the entire carillon as an ensemble. It also yields a powerful parametric synthesis model for reproducing bell sounds and bell-based audio effects.

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