International Professional University of Technology in Nagoya Repository
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Modelling the Extremely Low Frequencies Magnetic Fields Times Series Exposure by Segmentation
No full textNational audienceELFSTAT project, founded by the French ANSES (2015-2019, Grant agreement n. 2015/1/202), aims at characterizing children’s exposure to Extremely Low Frequency Magnetic Fields (ELF-MF) in real exposure scenarios using stochastic approaches.The present paper gives details about the first step of the project: this step aims at developing stochastic models to model personal exposure from a dataset of recorded ELF-MF signals
A model of perceived dynamic range for HDR images
No full textInternational audienceFor High Dynamic Range (HDR) content, the dynamic range of an image is an important characteristic in algorithm design and validation, analysis of aesthetic attributes and content selection. Traditionally, it has been computed as the ratio between the maximum and minimum pixel luminance, a purely objective measure; however, the human visual system's perception of dynamic range is more complex and has been largely neglected in the literature. In this paper, a new methodology for measuring perceived dynamic range (PDR) of chromatic and achromatic HDR images is proposed. PDR can benefit HDR in a number of ways: for evaluating inverse tone mapping operators and HDR compression methods; aesthetically; or as a parameter for content selection in perceptual studies. A subjective study was conducted on a data set of 36 chromatic and achromatic HDR images. Results showed a strong agreement across participants' allocated scores. In addition, a high correlation between ratings of the chromatic and achromatic stimuli was found. Based on the results from a pilot study, five objective measures (pixel-based dynamic range, image key, area of bright regions, contrast and colorfulness) were selected as candidates for a PDR predictor model; two of which have been found to be significant contributors to the model. Our analyses show that this model performs better than individual metrics for both achromatic and chromatic stimuli
Quantifying the Memory Effects of Power Amplifiers: EVM Closed-Form Derivations of Multicarrier Signals
No full textInternational audienceThis letter deals with the analysis of the memory effects of the Power Amplifier (PA) on multicarrier signals. We analytically derive the expressions of the Error Vector Magnitude (EVM) of amplified signals jointly considering a memory polynomial PA model and clipping effects. We provide analytical EVM expressions that depend on the PA coefficients, PA order, and memory depth as well as the clipping threshold of the input signal. These analytical expressions are new general formulas which allow to predict in-band distortions at the PA output
Towards Computational Photomechanics
No full textInternational audienceExperimental mechanics is currently experiencing a revolution: the rapid development and spread of camera-based measurement systems, which enable experimentalists to visualise the displacement and strain distributions occurring in structures or specimens subjected to a load. In order to obtain information that is as valuable as that provided by numerical models, we need to move on from lowly to highly-resolved maps, and from qualitative to quantitative measuring tools. To this end, new mathematical results and algorithms are needed
Séparation aveugle de source : de l'instantané au convolutif
No full textBlind source separation (BSS) consists of estimating the source signals only from the observed mixtures. The problem can be divided into two categories according to the mixing model: instantaneous mixtures, where delay and reverberation (multi-path effect) are not taken into account, and convolutive mixtures which are more general but more complicated. Moreover, the additive noise at the sensor level and the underdetermined setting, where there are fewer sensors than the sources, make the problem even more difficult.In this thesis, we first studied the link between two existing methods for instantaneous mixtures: independent component analysis (ICA) and sparse component analysis (SCA). We then proposed a new formulation that works in both determined and underdetermined cases, with and without noise. Numerical evaluations show the advantage of the proposed approaches.Secondly, the proposed formulation is generalized for convolutive mixtures with speech signals. By integrating a new approximation model, the proposed algorithms work better than existing methods, especially in noisy and/or high reverberation scenarios.Then, we take into account the technique of morphological decomposition and the use of structured sparsity which leads to algorithms that can better exploit the structures of audio signals. Such approaches are tested for underdetermined convolutive mixtures in a non-blind scenario.At last, being benefited from the NMF model, we combined the low-rank and sparsity assumption and proposed new approaches for under-determined convolutive mixtures. The experiments illustrate the good performance of the proposed algorithms for music signals, especially in strong reverberation scenarios.La séparation aveugle de source consiste à estimer les signaux de sources uniquement à partir des mélanges observés. Le problème peut être séparé en deux catégories en fonction du modèle de mélange: mélanges instantanés, où le retard et la réverbération (effet multi-chemin) ne sont pas pris en compte, et des mélanges convolutives qui sont plus généraux mais plus compliqués. De plus, le bruit additif au niveaux des capteurs et le réglage sous-déterminé, où il y a moins de capteurs que les sources, rendent le problème encore plus difficile.Dans cette thèse, tout d'abord, nous avons étudié le lien entre deux méthodes existantes pour les mélanges instantanés: analyse des composants indépendants (ICA) et analyse des composant parcimonieux (SCA). Nous avons ensuite proposé une nouveau formulation qui fonctionne dans les cas déterminés et sous-déterminés, avec et sans bruit. Les évaluations numériques montrent l'avantage des approches proposées.Deuxièmement, la formulation proposés est généralisés pour les mélanges convolutifs avec des signaux de parole. En intégrant un nouveau modèle d'approximation, les algorithmes proposés fonctionnent mieux que les méthodes existantes, en particulier dans des scénarios bruyant et / ou de forte réverbération.Ensuite, on prend en compte la technique de décomposition morphologique et l'utilisation de parcimonie structurée qui conduit à des algorithmes qui peuvent mieux exploiter les structures des signaux audio. De telles approches sont testées pour des mélanges convolutifs sous-déterminés dans un scénario non-aveugle.Enfin, en bénéficiant du modèle NMF (factorisation en matrice non-négative), nous avons combiné l'hypothèse de faible-rang et de parcimonie et proposé de nouvelles approches pour les mélanges convolutifs sous-déterminés. Les expériences illustrent la bonne performance des algorithmes proposés pour les signaux de musique, en particulier dans des scénarios de forte réverbération
Implementation and Evaluation of a Controller-Based Forwarding Scheme for NDN
No full textInternational audienceNamed-Data Networking (NDN) is a novel clean-slate architecture for Future Internet. It has been designed to take into account a new use of the Internet and especially accessing content for a large number of users, and it integrates several features such as in-network caching, security or multipath. As NDN relies on content names instead of host address, it cannot rely on traditional Internet routing, and it is therefore essential to propose a routing scheme adapted for NDN. To this end, in this paper, we present SRSC, our SDN-based Routing Scheme for CCN/NDN and its implementation. SRSC relies on the SDN paradigm.A controller is responsible to forward decisions and to set up rules into NDN nodes. We implement SRSC into NDNx and we also deploy an NDN testbed within a virtual environment and real ISP topology in order to evaluate the performances of our proposal with real-world experiments. We demonstrate the feasibility of SRSC and its ability to forward Interest messages in a fully deployed NDN environment, while keeping low overhead and computation time and high caching performances
Delay Analysis of AVB traffic in Time-Sensitive Networks (TSN)
No full textInternational audienceFuture autonomous vehicles and ADAS (Advanced Driver Assistance Systems) need real-time audio and video transmission together with control data traac (CDT). Audio/video stream delay analysis has been largely investigated in AVB (Audio Video Bridging) context, but not yet with the presence of the CDT in the new TSN context. In this paper we present a local delay analysis of AVB frames under hierarchical scheduling of credit-based shaping and time-aware shaping on TSN switches. We present the eeects of time aware shaping on AVB traac, how it changes the relative order of transmission of frames leading to bursts and worst case scenarios for lower priority streams. We also show that these bursts are upper-bounded by the Credit-Bases Shaper, hence the worst-case transmissions delay of a given stream is also upper-bounded. We present the analysis to compute the worst case delay for a frame, as well as the feasibility condition necessary for the analysis to be applied. Our methods (analysis and simulation) are applied to an automotive use case, which is deened within the Eurostars RETINA project, and where both control data traac and AVB traac must be guaranteed. CCS CONCEPTS • Computer systems organization →Embedded systems; • Networks →Network reliability
On the Complexity of the Uniqueness of Solutions in Graph Problems
No full textRapport interne Telecom ParisTech-2017D001, Paris, France, 119 page
A robust nonlinear position observer for synchronous motors with relaxed excitation conditions
No full textInternational audienceA robust, nonlinear and globally convergent rotor position observer for surface-mounted permanent magnet synchronous motors was recently proposed by the authors. The key feature of this observer is that it requires only the knowledge of the motor's resistance and inductance. Using some particular properties of the mathematical model it is shown that the problem of state observation can be translated into one of estimation of two constant parameters, which is carried out with a standard gradient algorithm. In this work, we propose to replace this estimator with a new one called dynamic regressor extension and mixing, which has the following advantages with respect to gradient estimators: (1) the stringent persistence of excitation (PE) condition of the regressor is not necessary to ensure parameter convergence; (2) the latter is guaranteed requiring instead a non-square-integrability condition that has a clear physical meaning in terms of signal energy; (3) if the regressor is PE, the new observer (like the old one) ensures convergence is exponential, entailing some robustness properties to the observer; (4) the new estimator includes an additional filter that constitutes an additional degree of freedom to satisfy the non-square integrability condition. Realistic simulation results show significant performance improvement of the position observer using the new parameter estimator, with a less oscillatory behaviour and a faster convergence speed