Remarques sur l'adaptativité des représentations temps- fréquence

International audience– Nous nous intéressons auprobì eme de l'adaptation au signal analysé de la fenêtre d'une représentation de Fourier a court terme dans deux cas de figure: adaptations globale et locale. Nous montrons que la représentation " optimale " dépend forte-ment du crit ere choisi dans le cas de l'optimisation globale, et qu'une optimisation locale peut permettre de pallier ceprobì eme, au moins dans certaines situations. L' intérêt de telles techniques est illustré par un exemple de séparation de composantes. Abstract – We consider the problem of window optimization for short time Fourier transform in two different frameworks: global and local optimization. We show that in the global situation, where the window is adapted to the complete signal, the " optimal " representation depends strongly on the chosen criterion. This suggests to turn to procedures which adapt the window to specific " components " of the signal, and we show that such approaches overcome at least partially the above mentioned shortcoming. The interest of such techniques is illustrated by an example of separation of components

Faster Sound Stream Segmentation In Musicians Than In Nonmusicians

The musician's brain is considered as a good model of brain plasticity as musical training is known to modify auditory perception and related cortical organization. Here, we show that music-related modifications can also extend beyond motor and auditory processing and generalize (transfer) to speech processing. Previous studies have shown that adults and newborns can segment a continuous stream of linguistic and non-linguistic stimuli based only on probabilities of occurrence between adjacent syllables, tones or timbres. The paradigm classically used in these studies consists of a passive exposure phase followed by a testing phase. By using both behavioural and electrophysiological measures, we recently showed that adult musicians and musically trained children outperform nonmusicians in the test following brief exposure to an artificial sung language. However, the behavioural test does not allow for studying the learning process per se but rather the result of the learning. In the present study, we analyze the electrophysiological learning curves that are the ongoing brain dynamics recorded as the learning is taking place. While musicians show an inverted U shaped learning curve, nonmusicians show a linear learning curve. Analyses of Event-Related Potentials (ERPs) allow for a greater understanding of how and when musical training can improve speech segmentation. These results bring evidence of enhanced neural sensitivity to statistical regularities in musicians and support the hypothesis of positive transfer of training effect from music to sound stream segmentation in general

The Pole Behaviour of the Phase Derivative of the Short-Time Fourier Transform

The short-time Fourier transform (STFT) is a time-frequency representation widely used in applications, for example in audio signal processing. Recently it has been shown that not only the amplitude, but also the phase of this representation can be successfully exploited for improved analysis and processing. In this paper we describe a rather peculiar pole phenomenon in the phase derivative, a recurring pattern that appears in a characteristic way in the neighborhood around any of the zeros of the STFT, a negative peak followed by a positive one. We describe this phenomenon numerically and provide a complete analytical explanation.Comment: 15 pages, 4 figures; Applied and Computational Harmonic Analysis (in press), available online 22 October 201

Neo: an object model for handling electrophysiology data in multiple formats

Neuroscientists use many different software tools to acquire, analyze and visualize electrophysiological signals. However, incompatible data models and file formats make it difficult to exchange data between these tools. This reduces scientific productivity, renders potentially useful analysis methods inaccessible and impedes collaboration between labs. A common representation of the core data would improve interoperability and facilitate data-sharing. To that end, we propose here a language-independent object model, named “Neo,” suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. As a concrete instantiation of this object model we have developed an open source implementation in the Python programming language. In addition to representing electrophysiology data in memory for the purposes of analysis and visualization, the Python implementation provides a set of input/output (IO) modules for reading/writing the data from/to a variety of commonly used file formats. Support is included for formats produced by most of the major manufacturers of electrophysiology recording equipment and also for more generic formats such as MATLAB. Data representation and data analysis are conceptually separate: it is easier to write robust analysis code if it is focused on analysis and relies on an underlying package to handle data representation. For that reason, and also to be as lightweight as possible, the Neo object model and the associated Python package are deliberately limited to representation of data, with no functions for data analysis or visualization. Software for neurophysiology data analysis and visualization built on top of Neo automatically gains the benefits of interoperability, easier data sharing and automatic format conversion; there is already a burgeoning ecosystem of such tools. We intend that Neo should become the standard basis for Python tools in neurophysiology.EC/FP7/269921/EU/Brain-inspired multiscale computation in neuromorphic hybrid systems/BrainScaleSDFG, 103586207, GRK 1589: Verarbeitung sensorischer Informationen in neuronalen SystemenBMBF, 01GQ1302, Nationaler Neuroinformatik Knote

Handling Metadata in a Neurophysiology Laboratory

To date, non-reproducibility of neurophysiological research is a matter of intense discussion in the scientific community. A crucial component to enhance reproducibility is to comprehensively collect and store metadata, that is, all information about the experiment, the data, and the applied preprocessing steps on the data, such that they can be accessed and shared in a consistent and simple manner. However, the complexity of experiments, the highly specialized analysis workflows and a lack of knowledge on how to make use of supporting software tools often overburden researchers to perform such a detailed documentation. For this reason, the collected metadata are often incomplete, incomprehensible for outsiders or ambiguous. Based on our research experience in dealing with diverse datasets, we here provide conceptual and technical guidance to overcome the challenges associated with the collection, organization, and storage of metadata in a neurophysiology laboratory. Through the concrete example of managing the metadata of a complex experiment that yields multi-channel recordings from monkeys performing a behavioral motor task, we practically demonstrate the implementation of these approaches and solutions with the intention that they may be generalized to other projects. Moreover, we detail five use cases that demonstrate the resulting benefits of constructing a well-organized metadata collection when processing or analyzing the recorded data, in particular when these are shared between laboratories in a modern scientific collaboration. Finally, we suggest an adaptable workflow to accumulate, structure and store metadata from different sources using, by way of example, the odML metadata framework

Time-Frequency Jigsaw Puzzle: adaptive multiwindow and multilayered Gabor expansions

International audienceWe describe a new adaptive multiwindow Gabor expansion, which dynamically adapts the windows to the signal's features in time-frequency space. The adaptation is based upon local time-frequency sparsity criteria, and also yields as by-product an expansion of the signal into layers corresponding to different windows. As an illustration, we show that simply using two different windows with different sizes leads to decompositions of audio signals into transient and tonal layers. We also discuss potential applications to transient detection and denoising

Représentation et traitement temps-fréquence des signaux audionumériques pour des applications de design sonore

Spécialité : Acoustique, Traitement du signal et Informatique Appliqués à la Musique (ATIAM)This thesis describes a number of theoretical issues, algorithms and software developments in view of industrial sound design applications. Audio processing for sound design involves a set of processing steps, including signal analysis, representation, modification, and synthesis. This document describes contributions to these different steps.The first part deals with time-frequency representations, focusing on the case of atomic decompositions (Gabor transform, wavelets, ...). We show how these approaches can be modified to bring more freedom in the decomposition, enabling to adapt the decomposition to given signal or class of signals, or a specific problem. We also show how these elements can be used in the context of supervised and unsupervised adaptive algorithms.The second part deals with dectection and estimation of structured components, starting from an adapted representation such as the ones proposed in the first part. We study the cases of locally harmonic components and transient components.The third part describes the main aspects of software tools developed as part of this work. This software implements several of the new approaches described in the first two parts. It also shortly describes a few examples of processing for sound design done in an industrial context using the tools described in this thesis.Cette thèse décrit un certain nombre de développements théoriques, algorithmiques et logiciels en vue d’applications au design sonore industriel. Le design sonore met en œuvre une série de traitements effectués sur des signaux audionumériques, allant de la représentation à la synthèse, en passant par des étapes d’analyse et de modification.Ce mémoire présente des contributions aux différentes étapes de traitement.La première partie est consacrée au problème de représentation, en se limitant au cadre des représentations temps-fréquence “atomiques” (transformation de Gabor, ondelettes, ...). On montre comment ces approches peuvent être modifiées pour y introduire davantage de souplesse, ce qui permet de les adapter à un signal, une classe de signaux, ou une problématique donnés. On montre également comment ces techniques peuvent être mises en œuvre dans le cadre d’algorithmes adaptatifs, supervisés ou non supervisés.La deuxième partie est consacrée à la détection et l’estimation de composantes structurées dans les signaux, à partir de représentations adaptées telles que celles développées dans la première partie. On considère en particulier le cas de signaux localement harmoniques, et celui de signaux transitoires.La troisième partie décrit les grandes lignes d’un développement logiciel effectué dans le cadre de ce travail, et mettant en œuvre des approches décrites dans les deux premières parties du mémoire. Elle présente également des exemples de traitements réalisés dans un cadre industriel

Représentation et traitement temps-fréquence des signaux audionumériques pour des applications de design sonore

Spécialité : Acoustique, Traitement du signal et Informatique Appliqués à la Musique (ATIAM)This thesis describes a number of theoretical issues, algorithms and software developments in view of industrial sound design applications. Audio processing for sound design involves a set of processing steps, including signal analysis, representation, modification, and synthesis. This document describes contributions to these different steps.The first part deals with time-frequency representations, focusing on the case of atomic decompositions (Gabor transform, wavelets, ...). We show how these approaches can be modified to bring more freedom in the decomposition, enabling to adapt the decomposition to given signal or class of signals, or a specific problem. We also show how these elements can be used in the context of supervised and unsupervised adaptive algorithms.The second part deals with dectection and estimation of structured components, starting from an adapted representation such as the ones proposed in the first part. We study the cases of locally harmonic components and transient components.The third part describes the main aspects of software tools developed as part of this work. This software implements several of the new approaches described in the first two parts. It also shortly describes a few examples of processing for sound design done in an industrial context using the tools described in this thesis.Cette thèse décrit un certain nombre de développements théoriques, algorithmiques et logiciels en vue d’applications au design sonore industriel. Le design sonore met en œuvre une série de traitements effectués sur des signaux audionumériques, allant de la représentation à la synthèse, en passant par des étapes d’analyse et de modification.Ce mémoire présente des contributions aux différentes étapes de traitement.La première partie est consacrée au problème de représentation, en se limitant au cadre des représentations temps-fréquence “atomiques” (transformation de Gabor, ondelettes, ...). On montre comment ces approches peuvent être modifiées pour y introduire davantage de souplesse, ce qui permet de les adapter à un signal, une classe de signaux, ou une problématique donnés. On montre également comment ces techniques peuvent être mises en œuvre dans le cadre d’algorithmes adaptatifs, supervisés ou non supervisés.La deuxième partie est consacrée à la détection et l’estimation de composantes structurées dans les signaux, à partir de représentations adaptées telles que celles développées dans la première partie. On considère en particulier le cas de signaux localement harmoniques, et celui de signaux transitoires.La troisième partie décrit les grandes lignes d’un développement logiciel effectué dans le cadre de ce travail, et mettant en œuvre des approches décrites dans les deux premières parties du mémoire. Elle présente également des exemples de traitements réalisés dans un cadre industriel

MinCoverPetri

MinCoverPetri is a command-line application for the fast computation of the minimal coverability set of place/transition (P/T) Petri nets.It can process P/T Petri nets stored in the Petri Net Markup Language (PNML) file format defined by the standard ISO/IEC 15909 Part 2.See pnml.org for details about this format.It uses the monotone pruning algorithm proposed in the article:Minimal Coverability Set for Petri Nets: Karp and Miller Algorithm with Pruning.P.-A. Reynier and F. Servais.In Fundamenta Informaticae, vol. 122, no. 1-2, pp. 1-30, IOS Press,2013.DOI: 10.3233/FI-2013-781MinCoverPetri is developed in C++ by the development team of the LIS