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<dc:title xml:lang="fr">Peut-on entendre la forme d'une pièce ? : Reconstruction de la géométrie d'une salle à partir de mesures acoustiques par super-résolution et optimisation de forme</dc:title>
<dcterms:alternative xml:lang="en">Can one hear the shape of a room ? : Room geometry reconstruction from acoustic measurements using super-resolution and shape optimization</dcterms:alternative>
<dc:subject xml:lang="fr">Forme de salle</dc:subject>
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<dc:subject xml:lang="fr">Réponse impulsionnelle de salle</dc:subject>
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<dc:subject xml:lang="fr">Optimisation de forme</dc:subject>
<dc:subject xml:lang="fr">Méthode des solutions fondamentales</dc:subject>
<dc:subject xml:lang="fr">Problème inverse</dc:subject>
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<dc:subject xml:lang="en">Echoes</dc:subject>
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<dc:subject xml:lang="en">Room Shape</dc:subject>
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<dcterms:abstract xml:lang="fr">Cette thèse aborde le problème inverse de la reconstruction de la géométrie d’une pièce à partir de mesures acoustiques. Plus précisément, nous nous concentrons sur les Réponses Impulsionnelles de Salle. Nous développons deux approches distinctes pour résoudre ce problème. La première approche considère des pièces parallélépipédiques avec des murs réfléchissants et repose sur la méthode dite des Sources Images. Nous proposons un cadre novateur basé sur l’algorithme Frank-Wolfe pour reconstruire les positions 3D des sources images en résolvant un problème d’optimisation convexe dans l’espace des mesures de Radon. La deuxième approche s’étend à des formes de pièce plus générales en formulant le problème inverse comme un problème d’optimisation de forme, où la géométrie de la pièce est optimisée en minimisant les écarts entre des observations dans le domaine fréquentiel et la solution de l’équation de Helmholtz définie sur le domaine de la pièce.</dcterms:abstract>
<dcterms:abstract xml:lang="en">This thesis addresses the inverse problem of reconstructing the geometry of a room from acoustic measurements. Specifically, we focus on Room Impulse Responses. We develop two distinct approaches to tackle this problem. The first approach considers cuboid rooms with reflective walls and is based on the so-called Image Source Method. We propose a novel framework, utilizing the Frank-Wolfe algorithm, to reconstruct the 3D positions of image sources in a gridless manner by solving a convex optimization problem in the space of Radon measures. The second approach extends to more general room shapes. The inverse problem is formulated as a shape optimization problem, where the room geometry is refined by minimizing discrepancies between frequency-domain observations and the solution of the Helmholtz equation defined on the room domain.</dcterms:abstract>
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