Download Using nonlinear amplifier simulation in dynamic range controllers Amplifying devices where the gain is automatically controlled by the level of the input signal performs dynamics processing. Non-linear components simulating tube amplifiers can be used in these devices to make musical signal audibly dense [1]. This paper deals with the simulation of tube amplifiers using the power polynomial approximation of transfer characteristic and their use in dynamic range controllers. The influence of various non-linear amplifying devices simulating tube amplifiers on the output signal spectrum of dynamic effects is presented as well.
Download Real-Time Guitar Tube Amplifier Simulation using an Approximation of Differential Equations Digital simulation of guitar tube amplifiers is still an opened topic. The efficient implementation of several parts of the guitar amplifier is presented in this paper. This implementation is based on the pre-computation of the solution of the nonlinear differential system and further approximation of the solution. It reduces the computational complexity while the accuracy is comparable with the numerical solution. The method is used for simulation of different parts of the guitar amplifier, namely a triode preamp stage, a phase splitter and a push-pull amplifier. Finally, the results and comparison with other methods are discussed.
Download Simulation of a Vacuum-Tube Push-Pull Guitar Power Amplifier Power amplifiers play an important role in producing of guitar sound. Therefore, the modeling of guitar amplifiers must also include a power amplifier. In this paper, a push-pull guitar tube power amplifier, including an output transformer and influence of a loudspeaker, is simulated in different levels of complexity in order to find a simplified model of an amplifier with regards to accuracy and computational efficiency.
Download Neural Grey-Box Guitar Amplifier Modelling with Limited Data This paper combines recurrent neural networks (RNNs) with the discretised Kirchhoff nodal analysis (DK-method) to create a grey-box guitar amplifier model. Both the objective and subjective results suggest that the proposed model is able to outperform a baseline black-box RNN model in the task of modelling a guitar amplifier, including realistically recreating the behaviour of the amplifier equaliser circuit, whilst requiring significantly less training data. Furthermore, we adapt the linear part of the DK-method in a deep learning scenario to derive multiple state-space filters simultaneously. We frequency sample the filter transfer functions in parallel and perform frequency domain filtering to considerably reduce the required training times compared to recursive state-space filtering. This study shows that it is a powerful idea to separately model the linear and nonlinear parts of a guitar amplifier using supervised learning.
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 Fast Temporal Convolutions for Real-Time Audio Signal Processing This paper introduces the possibilities of optimizing neural network convolutional layers for modeling nonlinear audio systems and effects. Enhanced methods for real-time dilated convolutions are presented to achieve faster signal processing times than in previous work. Due to the improved implementation of convolutional layers, a significant decrease in computational requirements was observed and validated on different configurations of single layers with dilated convolutions and WaveNet-style feedforward neural network models. In most cases, equivalent signal processing times were achieved to those using recurrent neural networks with Long Short-Term Memory units and Gated Recurrent Units, which are considered state-of-the-art in the field of black-box virtual analog modeling.
Download Modelling digital musical effects for signal processors, based on real effect manifestation analysis For quite some time in the area of commercial utilization of digital audio effects, efforts have emerged to create simulate by software analog effects and effect processors This paper deals with the analysis of musical effects, the design of algorithms for simulating these effects, and their realization on both digital signal processors and the PC platform in the form of plug-in modules for the DirectX environment. It also deals with the problem of controlling the effect parameters and with subjective testing of algorithms, and it examines the fidelity of simulated effects as compared with the original.
Download Optimizing Digital Musical Effect Implementation for Multiple Processor DSP Systems In the area of digital musical effect implementation, attention has lately been focused on computer workstations designed for digital processing of sound, which perform all operations with audio signals in real time. They are in fact a combination of powerful computer program and hardware cards with digital signal processors. Thanks to the power enhancement of personal computer core, performing these operations in the CPU is currently possible. However, in most cases, digital signal processors are still used for these purposes because digital musical effect modelling is more effective and more precise with the digital signal processor. In addition to this, processing in digital signal processor saves the CPU computing power for other functions.