Download Circuit Simulation with Inductors and Transformers Based on the Jiles-Atherton Model of Magnetization The sound of a vacuum tube guitar amplifier may be significantly influenced by the non-linear behavior of its output transformer, which therefore should also be considered in digital simulations. In this work, we develop a model for inductors and transformers with the magnetization following the model of Jiles and Atherton. For this purpose, the original magnetization model is rewritten to a differential equation with respect to time which can then easily be integrated into a previously developed circuit simulation framework. The model thus derived is then exercised in the simulation of three simple circuits where it shows the expected behavior.
Download Simulation of Fender Type Guitar Preamp using Approximation and State-Space Model This paper deals with usage of approximations for simulation of more complex audio circuits. A Fender type guitar preamp was chosen as a case study. This circuit contains two tubes and thus four nonlinear functions as well as it is a parametric circuit because of an integrated tone stack. A state-space approach was used for simulation and further, precomputed solution is approximated using nonuniform cubic splines.
Download Physical Modeling of the MXR Phase 90 Guitar Effect Pedal In this study, a famous boxed effect pedal, also called stompbox, for electrical guitars is analyzed and simulated. The nodal DK method is used to create a non-linear state-space system with Matlab as a physical model for the MXR Phase 90 guitar effect pedal. A crucial component of the effect are Junction Field Effect Transistors (JFETs) which are used as variable resistors to dynamically vary the phase-shift characteristic of an allpass-filter cascade. So far, virtual analog modeling in the context of audio has mainly been applied to diode-clippers and vacuum tube circuits. This work shows an efficient way of describing the nonlinear behavior of JFETs, which are wide-spread in audio devices. To demonstrate the applicability of the proposed physical model, a real-time VST audio plug-in was implemented.
Download Discretization of Parametric Analog Circuits for Real-Time Simulations The real-time simulation of analog circuits by digital systems becomes problematic when parametric components like potentiometers are involved. In this case the coefficients defining the digital system will change and have to be adapted. One common solution is to recalculate the coefficients in real-time, a possibly computationally expensive operation. With a view to the simulation using state-space representations, two parametric subcircuits found in typical guitar amplifiers are analyzed, namely the tone stack, a linear passive network used as simple equalizer and a distorting preamplifier, limiting the signal amplitude with LEDs. Solutions using trapezoidal rule discretization are presented and discussed. It is shown, that the computational costs in case of recalculation of the coefficients are reduced compared to the related DK-method, due to minimized matrix formulations. The simulation results are compared to reference data and show good match.
Download The Influence of Small Variations in a Simplified Guitar Amplifier Model A strongly simplified guitar amplifier model, consisting of four stages, is presented. The exponential sweep technique is used to measure the frequency dependent harmonic spectra. The influence of small variations of the system parameters on the harmonic components is analyzed. The differences of the spectra are explained and visualized.
Download Automatic Decomposition of Non-linear Equation Systems in Audio Effect Circuit Simulation In the digital simulation of non-linear audio effect circuits, the arising non-linear equation system generally poses the main challenge for a computationally cheap implementation. As the computational complexity grows super-linearly with the number of equations, it is beneficial to decompose the equation system into several smaller systems, if possible. In this paper we therefore develop an approach to determine such a decomposition automatically. We limit ourselves to cases where an exact decomposition is possible, however, and do not consider approximate decompositions.