French-Austrian bilateral research project funded by the French National Agency of Research (ANR) and the Austrian Science Fund (FWF, project no. I 1362-N30). The project involves two academic partners, namely the Laboratory of Mechanics and Acoustics (LMA - CNRS UPR 7051, France) and the Acoustics Research Institute. At the ARI, two research groups are involved in the project: the Mathematics and Signal Processing in Acoustics and the Psychoacoustics and Experimental Audiology groups.
Principal investigators: Thibaud Necciari (ARI), Piotr Majdak (ARI) and Olivier Derrien (LMA).
Running period: 2014-2017 (project started on March 1, 2014).
One of the greatest challenges in signal processing is to develop efficient signal representations. An efficient representation extracts relevant information and describes it with a minimal amount of data. In the specific context of sound processing, and especially in audio coding, where the goal is to minimize the size of binary data required for storage or transmission, it is desirable that the representation takes into account human auditory perception and allows reconstruction with a controlled amount of perceived distortion. Over the last decades, many psychoacoustical studies investigated auditory masking, an important property of auditory perception. Masking refers to the degradation of the detection threshold of a sound in presence of another sound. The results were used to develop models of either spectral or temporal masking. Attempts were made to simply combine these models to account for time-frequency (t-f) masking effects in perceptual audio codecs. We recently conducted psychoacoustical studies on t-f masking. They revealed the inaccuracy of those models which revealed the inaccuracy of such simple models. These new data on t-f masking represent a crucial basis to account for masking effects in t-f representations of sounds. Although t-f representations are standard tools in audio processing, the development of a t-f representation of audio signals that is mathematically-founded, perception-based, perfectly invertible, and possibly with a minimum amount of redundancy, remains a challenge. POTION thus addresses the following questions:
POTION is structured in three main tasks:
More information on the project can be found on the POTION web page.
Diese Seite ist eine Projektbeschreibung und als solche in englischer Sprache verfasst.
This international, multi-disciplinary and team-oriented project will expand the group Mathematics and Acoustical Signal Processing at the Acoustic Research Institute in cooperation with NuHAG Vienna (Hans G. Feichtinger, M. Dörfler, K. Gröchenig), Institute of Telecommunication Vienna (Franz Hlawatsch), LATP Marseille (Bruno Torrésani) LMA (Richard Kronland-Martinet). CAHR (Torsten Dau, Peter Soendergaard), the FYMA Louvain-la-Neuve (Jean-Pierre Antoine), AG Numerics (Stephan Dahlke), School of Electrical Engineering and Computer Science (Damian Marelli) as well as the BKA Wiesbaden (Timo Becker).
We live in the age of information where the analysis, classification, and transmission of information is f essential importance. Signal processing tools and algorithms form the backbone of important technologieslike MP3, digital television, mobile phones and wireless networking. Many signal processing algorithms have been adapted for applications in audio and acoustics, also taking into account theproperties of the human auditory system.
The mathematical concept of frames describes a theoretical background for signal processing. Frames are generalizations of orthonormal bases that give more freedom for the analysis and modificationof information - however, this concept is still not firmly rooted in applied research. The link between the mathematical frame theory, the signal processing algorithms, their implementations andfinally acoustical applications is a very promising, synergetic combination of research in different fields.
Therefore the main goal of this multidisciplinary project is to
-> Establish Frame Theory as Theoretical Backbone of Acoustical Modeling
in particular in psychoacoustics, phonetic and computational acoustics as well as audio engineering.
For this auspicious connection of disciplines, FLAME will produce substantial impact on both the heory and applied research.
The theory-based part of FLAME consists of the following topics:
The application-oriented part of FLAME consists of:
From many previous applications, it is known that inverse problems often require a regularization that makes the inversion numerically stable. In this project, sequences that allow a bounded, injective analysis (that is not boundedly invertible) are investigated, .
Even for general sequences, analysis operator and synthesis operator can be defined. The first part of this project will investigate the most general results of these definitions. For example, it can be shown that the analysis operator is always a closed operator. Although it can be shown that the existence of another sequence that allows a perfect reconstruction fit can not be bounded, the question of how to construct such a "dual sequence" will be investigated.
Such sequences have already found applications in wavelet analysis, in which dual sequences were constructed algorithmically. Also, the original system investigated by Gabor with a redundancy of 1 satisfies this condition.
Funded by the Vienna Science and Technology Fund (WWTF) within the "Mathematics and …2016" Call (MA16-053)
Principal Investigator: Georg Tauböck
Co-Principal Investigator: Peter Balazs
Duration: 01.07.2017 – 01.07.2021
Signal processing is a key technology that forms the backbone of important developments like MP3, digital television, mobile communications, and wireless networking and is thus of exceptional relevance to economy and society in general. The overall goal of the proposed project is to derive highly efficient signal processing algorithms and to tailor them to dedicated applications in acoustics. We will develop methods that are able to exploit structural properties in infinite-dimensional signal spaces, since typically ad hoc restrictions to finite dimensions do not sufficiently preserve physically available structure. The approach adopted in this project is based on a combination of the powerful mathematical methodologies frame theory (FT), compressive sensing (CS), and information theory (IT). In particular, we aim at extending finite-dimensional CS methods to infinite dimensions, while fully maintaining their structure-exploiting power, even if only a finite number of variables are processed. We will pursue three acoustic applications, which will strongly benefit from the devised signal processing techniques, i.e., audio signal restoration, localization of sound sources, and underwater acoustic communications. The project is set up as an interdisciplinary endeavor in order to leverage the interrelations between mathematical foundations, CS, FT, IT, time-frequency representations, wave propagation, transceiver design, the human auditory system, and performance evaluation.
compressive sensing, frame theory, information theory, signal processing, super resolution, phase retrieval, audio, acoustics
Scientific and Technological Cooperation between Austria and Serbia (SRB 01/2018)
Duration of the project: 01.07.2018 - 30.06.2020
Acoustics Research Institute, ÖAW (Austria)
University of Vienna (Austria)
University of Novi Sad (Republic of Serbia)
Project website: http://nuhag.eu/anacres
Scientific and Technological Cooperation with Macedonia 2016-18
Project duration: 01.07.2016 – 30.06.2018
The main aim of the project is to combine the research areas of Frame Theory and Generalized Asymptotic Analysis.
Project partner institutions:
Acoustics Research Institute (ARI), Austrian Academy of Sciences, Vienna, Austria
Ss. Cyril and Methodius University, Skopje, The Former Yugoslav Republic of Macedonia
Diana T. Stoeva (Project coordinator Austria), Peter Balazs, Nicki Holighaus, Zdenek Prusa
Katerina Hadzi-Velkova Saneva (Project coordinator FYROM), Sanja Atanasova, Pavel Dimovski, Zoran Hadzi-Velkov, Bojan Prangoski, Biljana Stanoevska-Angelova, Daniel Velinov, Jasmina Veta Buralieva
Project Workshops and Activities:
1) Nov. 24-26, 2016, Ss. Cyril and Methodius University, Skopje
2) Nov. 15-19, 2017, ARI, Vienna
Research on project-related topics
3) April 14-19, 2018, ARI, Vienna
Research on project-related topics
ARI-Guest-Talk given at ARI on the 17th of April, 2018: Prof. Zoran Hadzi-Velkov, "The Emergence of Wireless Powered Communication Networks"
4) May 25-30, Ss. Cyril and Methodius University, Skopje
Research on project-related topics
Workshop "Women in mathematics in the Balkan region" (May 28 - May 29, Ss. Cyril and Methodius University, Skopje)
5) June 14-18, Ss. Cyril and Methodius University, Skopje
Research on project-related topics
Summer course "An Introduction to Frame Theory and the Large Time/Frequency Analysis Toolbox" (June 14-15), Lecturers: Diana Stoeva and Zdenek Prusa (from ARI)
6) Mini-Symposium "Frame Theory and Asymptotic Analysis" organized at the European Women in Mathematics General Meeting 2018, Karl-Franzens-Universität Graz, Austria, 3-7 September 2018.
7) November 17-20, 2018, ARI, Vienna
Work on project-related topics
Multilateral Scientific and Technological Cooperation in the Danube Region 2017-2018
Austria, Czech Republic, Republic of Serbia, and Slovak Republic
Project duration: 01.01.2017 - 31.12.2018
Project website: nuhag.eu/tifmofus
Numerous implementations and algorithms for time frequency analysis can be found in literature or on the internet. Most of them are either not well documented or no longer maintained. P. Soendergaard started to develop the Linear Time Frequency Toolbox for MATLAB. It is the goal of this project to find typical applications of this toolbox in acoustic applications, as well as incorporate successful, not-yet-implemented algorithms in STx.
The linear time-frequency toolbox is a small open-source Matlab toolbox with functions for working with Gabor frames for finite sequences. It includes 1D Discrete Gabor Transform (sampled STFT) with inverse. It works with full-length windows and short windows. It computes the canonical dual and canonical tight windows.
These algorithms are used for acoustic applications, like formants, data compression, or de-noising. These implementations are compared to the ones in STx, and will be implemented in this software package if they improve its performance.
General frame theory can be more specialized if a structure is imposed on the elements of the frame in question. One possible, very natural structure is sequences of shifts of the same function. In this project, irregular shifts are investigated.
In this project, the connection to irregular Gabor multipliers will be explored. Using the Kohn Nirenberg correspondence, the space spanned by Gabor multipliers is just a space spanned by translates. Furthermore, the special connection of the Gramian function and the Grame matrix for this case will be investigated.
A typical example of frames of translates is filter banks, which have constant shapes. For example, the phase vocoder corresponds to a filter bank with regular shifts. Introducing an irregular shift gives rise to a generalization of this analysis / synthesis system.
For many important applications - like virtual reality, communication, sound design, audio compression & coding, and hearing aids - a mathematical representation that matches or approximates the perception of the human auditory system is needed. For solving this critical and prominent problem, a trans-disciplinary approach is necessary. The goals of this project are:
This is a partner project of the ANR project senSons.
During the current project of efficiently calculating a resynthesis window and an iterative scheme for a finite element method algorithm for vibrations in soils and liquids, it became apparent that block matrices are a powerful tool to find numerically efficient algorithms.
In this project, the focus should be the investigation of the numeric features of block matrices. How can this structure be used to calculate or approximate the inverse of a matrix or its norm? How can this be used to speed up iterative schemes?
The results will be used for the two projects mentioned below: