Pultec EQP-1A Modeling with Wave Digital Filters

This thesis presents the development of a virtual analog model of the passive equal-izer section of the Pultec EQP-1A studio equalizer using Wave Digital Filters (WDF). The aim of the project was to provide an accurate and high performance open-source emulation of the circuitry and sound characteristics of the original hardware unit. The development process involved compiling the original unit’s schematics, gener-ating LTSpice simulations, and implementing the circuit in Python using the pywdf library and R-Type adaptors (a kind of adaptor used for modeling complex circuit junctions that cannot be classified as series or parallel). Since the R-Type adaptors greatly affected the performance of the model, the circuit was slightly modified to maintain its behavior without the need for R-Type adaptors. The frequency response of the Python prototype was compared to the LTSpice simulation showing that at sufficiently high sampling rates the error between the model and the simulations are minimal. The Python model was then ported to C++ using the JUCE framework and Chowdsp’s wdf library to generate a VST3 plug-in that can be loaded into digital audio worksta-tions. The plug-in has oversampling capabilities to preserve the adequate behavior of the circuit at frequencies close to Nyquist. The performance and accuracy of the Python model was measured, and the C++ im-plementation compared against another open-source implementation of the circuit using WDFs and R-Type adaptors (developed in the Faust programming language). The final EQP-1A Python model was 75% faster than our own one that used R-Type adaptors and the C++ implementation was 40% faster than the EQP-1A implemen-tation in Faust and a much more accurate emulation of the original circuit

Modelling of Supercapacitors: Factors Influencing Performance

The utilizable capacitance of Electrochemical Double Layer Capacitors (EDLCs) is a function of the frequency at which they are operated and this is strongly dependent on the construction and physical parameters of the device. We simulate the dynamic behavior of an EDLC using a spatially resolved model based on the porous electrode theory. The model of Verbrugge and Liu (J. Electrochem. Soc. 152, D79 (2005)) was extended with a dimension describing the transport into the carbon particle pores. Our results show a large influence of the electrode thickness (Le), separator thickness (Ls) and electrolyte conductivity (κ) on the performance of EDLCs. In agreement with experimental data, the time constant was an increasing function of Le and Ls and a decreasing function of κ. The main limitation was found to be on the scale of the whole cell, while transport into the particles became a limiting factor only if the particle size was unrealistically large. The results were generalized into a simplified relation allowing for a quick evaluation of performance for the design of new devices. This work provides an insight into the performance limitation of EDLCs and identifies the critical parameters to consider for both systems engineers and material scientists

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

Tunable coupling engineering between superconducting resonators: from sidebands to effective gauge fields

In this work we show that a tunable coupling between microwave resonators can be engineered by means of simple Josephson junctions circuits, such as dc- and rf-SQUIDs. We show that by controlling the time dependence of the coupling it is possible to switch on and off and modulate the cross-talk, boost the interaction towards the ultrastrong regime, as well as to engineer red and blue sideband couplings, nonlinear photon hopping and classical gauge fields. We discuss how these dynamically tunable superconducting circuits enable key applications in the fields of all optical quantum computing, continuous variable quantum information and quantum simulation - all within the reach of state of the art in circuit-QED experiments.Comment: 11 pages, 4 figure

Dynamic system characterization and design using mechanical impedance representations

Vibration testing is a critical aspect in the qualification of fieldable hardware as dynamic environments are typically design drivers. However, it is difficult to provide representative boundary conditions for component testing and the presence of an ill-matched boundary condition can alter the test outcomes. To achieve more realistic boundary conditions, test fixtures could be strategically designed such that they emulate the impedance of the next level of assembly. The body of work presented herein proposes various strategies for matching the drive point impedance of a target frequency response function (FRF) using undamped lumped parameter emulators. Two primary techniques have been developed to accomplish this impedance matching: a constrained exhaustive search algorithm and a constrained optimization algorithm. The constrained exhaustive search exploits newly identified high and low frequency limits in order to minimize the number of parameters that must be searched. The optimization algorithm provides an innovative methodology for the identification of a comprehensive and bounded design space and presents a novel implementation of particle swarm optimization that produces an optimized set of parameters for every identified physically realizable topology. This resultant emulator design space provides a basis from which low-complexity, low-cost fixtures can be constructed, thus offering an attainable path for better matching of boundary conditions and more representative vibration testing