Defence of dissertation in the field of Acoustics and Audio Signal Processing, M.Sc. (Tech.) Fabian Esqueda

2018-05-18 12:00:00 2018-05-18 23:59:59 Europe/Helsinki Defence of dissertation in the field of Acoustics and Audio Signal Processing, M.Sc. (Tech.) Fabian Esqueda The title of theis is “Aliasing Reduction in Nonlinear Audio Signal Processing” http://spa.aalto.fi/en/midcom-permalink-1e83728d42e4adc372811e8b19a5fc559a8d5c5d5c5 Maarintie 8, 02150, Espoo

The title of theis is “Aliasing Reduction in Nonlinear Audio Signal Processing”

18.05.2018 / 12:00
Hall AS1, Maarintie 8, 02150, Espoo, FI

Most real-world audio devices of interest in musical applications fall under the category of nonlinear systems. Examples of these devices include guitar and bass amplifiers, distortion pedals, dynamic range processors and vintage synthesizer circuits, to name but a few. Software emulations of these systems are susceptible to an unpleasant signal processing phenomenon known as aliasing. Aliasing is caused by the inherent limitations of digital signal processing, with oversampling being previously the only available (but expensive) approach to prevent it.

This thesis and its associated publications focus on the development of new digital signal processing techniques designed to reduce the level of aliasing introduced by static waveshaping nonlinearities. The main motivation behind this research is to incorporate these techniques within the bigger framework of virtual analog modeling, an exciting and popular area of study that seeks to emulate the behavior of vintage audio equipment in the digital domain. Virtual analog technologies fall in line with the digitization megatrend that has already taken over music, movies, photography and many other fields. Results presented in this thesis show the proposed methods effectively reduce aliasing caused by nonlinear processing and can help reduce, and in some cases even eliminate, the oversampling requirements.

Opponent:  Professor Udo Zölzer, Helmut Schmidt University, Germany

Supervisor:  Professor Vesa Välimäki, Aalto University School of Electrical Engineering, Department of Signal Processing and Acoustics.

Thesis website
Notice of dissertation defence
Contact information: Fabián Esqueda, fabian.esqueda@aalto.fi