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Two Approaches to Virtual Analog Modeling

Date: 
Thu, 04/20/2017 - 5:30pm - 7:30pm
Location: 
CCRMA Classroom
Event Type: 
DSP Seminar
This week's DSP seminar will feature THREE short conference-style talks on Virtual Analog Modeling. First, resident wave digital filter expert Mike Olsen and recent CCRMA alum Dr. Kurt James Werner will review papers on two aspects of the Wave Digital Filter formalism. Second, Ben Holmes (PhD candidate, Sonic Arts Research Centre, Queen's University Belfast) will present his work on characterizing physical Virtual Analog models of audio circuits.


Title: Wave Digital Filter Adaptors for Arbitrary Topologies and Multiport Linear Elements

Abstract: We present a Modified-Nodal-Analysis-derived method for developing Wave Digital Filter (WDF) adaptors corresponding to complicated (non-series/parallel) topologies that may include multi-port linear elements (e.g. controlled sources, transformers). A second method resolves non-computable (non-tree-like) arrangements of series/parallel adaptors. As with the familiar 3-port series and parallel adaptors, one port of each derived adaptor may be rendered reflection-free, making it acceptable for inclusion in a standard WDF tree. With these techniques, the class of acceptable reference circuits for WDF modeling is greatly expanded. This is demonstrated by case studies on circuits which were previously intractable with WDF methods: the Bassman tone stack and Tube Screamer tone/volume stage.

Bio: Dr. Kurt James Werner is a Lecturer in Audio at the Sonic Arts Research Centre (SARC) of Queen's University Belfast, where he joined the faculty of Arts, English, and Languages in early 2017. Before that he earned a PhD in Computer-Based Music Theory and Acoustic from Stanford University's CCRMA. As a researcher, he studies theoretical aspects of Wave Digital Filters and other virtual analog topics, computer modeling of circuit-bent instruments, and the history of music technology. As a composer of electro-acoustic/acousmatic music, his music references elements of chiptunes, musique concrète, circuit bending, algorithmic/generative composition, and breakbeat.


Title: Resolving Grouped Nonlinearities in Wave Digital Filters Using Iterative Techniques

Abstract: In this paper, iterative zero-finding techniques are proposed to resolve groups of nonlinearities occurring in Wave Digital Filters. Two variants of Newton’s method are proposed and their suitability towards solving the grouped nonlinearities is analyzed. The feasibility of the approach with implications for WDFs containing multiple nonlinearities is demonstrated via case studies investigating the mathematical properties and numerical performance of reference circuits containing diodes and transistors; asymmetric and symmetric diode clippers and a common emitter amplifier.

Bio: Michael Jørgen Olsen is a computer music researcher currently completing the second year of his Master of Arts in Music, Science and Technology degree at the Center for Computer Research in Music and Acoustics at Stanford University. His research interests include digital signal processing, digital synthesis techniques, virtual analog oscillators, time-frequency analysis, digital audio effects and physical modeling with a particular emphasis on the wave digital filter paradigm for analog circuit modeling. Prior to coming to Stanford, Mike graduated Magna Cum Laude from the University of California, San Diego with High Distinction in Mathematics and a Minor in Music with a focus on computer music.


Title: Replicating Vintage Guitar Pedals: Characterisation of Physical Virtual Analogue Circuits

Abstract: With the development of new modelling techniques capable of capturing higher levels of detail of audio circuits, a response is required from the techniques used to characterise said models. Particularly with regards to vintage guitar pedals, the specifics of a circuit can matter significantly, as it has been said that Jimi Hendrix would work through half a dozen fuzz pedals just to find the best sounding one. An approach to characterising physical models based on input/output measurements of a circuit will be discussed in the context of existing strategies, and how it attempts to offer improvements in automation, fidelity, and insight.

Bio: Ben Holmes is a PhD student at the Sonic Arts Research Centre (SARC) at Queen's University Belfast. He began his PhD in 2014, previously completing an undergraduate degree at the University of York. His PhD is focused on modelling of nonlinear audio effects. This primarily involves circuit modelling, real-time algorithm implementation, and also the measurement and analysis of audio effects.

FREE
Open to the Public
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