Latest Ph.D. Theseshttp://theses.eurasip.org/feeds/rss/theses/Most recent submissions to EURASIP's Library of Ph.D. Theses.en-usCopyright (c) 2017 EURASIPThu, 19 Oct 2017 09:15:50 +0300Compressed sensing and dimensionality reduction for unsupervised learninghttp://theses.eurasip.org/theses/733/compressed-sensing-and-dimensionality-reduction/This work aims at exploiting compressive sensing paradigms in order to reduce the cost of statistical learning tasks. We first provide a reminder of compressive sensing bases and describe some statistical analysis tasks using similar ideas. Then we describe a framework to perform parameter estimation on probabilistic mixture models in a case where training data is compressed to a fixed-size representation called a sketch. We formulate the estimation as a generalized inverse problem for which we propose a greedy algorithm. We experiment this framework and algorithm on an isotropic Gaussian mixture model. This proof of concept suggests the existence of theoretical recovery guarantees for sparse objects beyond the usual vector and matrix cases. We therefore study the generalization of linear inverse problems stability results on general signal models encompassing the standard cases and the sparse mixtures of probability distributions. We ...Bourrier, AnthonyThu, 19 Oct 2017 09:15:50 +0300http://theses.eurasip.org/theses/733/compressed-sensing-and-dimensionality-reduction/Audio motif detection for guided source separation. Application to movie soudtracks.http://theses.eurasip.org/theses/732/audio-motif-detection-for-guided-source/In audio signal processing, source separation consists in recovering the different audio sources that compose a given observed audio mixture. They are many techniques to estimate these sources and the more information are taken into account about them the more the separation is likely to be successful. One way to incorporate information on sources is the use of a reference signal which will give a first approximation of this source. This thesis aims to explore the theoretical and applied aspects of reference guided source separation. The proposed approach called SPotted REference based Separation (SPORES) explore the particular case where the references are obtained automatically by motif spotting, i.e., by a search of similar content. Such an approach is useful for contents with a certain redundancy or if a large database is be available. Fortunately, the current context often puts us ...Souviraà-Labastie NathanWed, 18 Oct 2017 17:46:40 +0300http://theses.eurasip.org/theses/732/audio-motif-detection-for-guided-source/Efficient matrices for signal processing and machine learning. (Matrices efficientes pour le traitement du signal et l'apprentissage automatique.)http://theses.eurasip.org/theses/731/efficient-matrices-for-signal-processing-and/Matrices, as natural representation of linear mappings in finite dimension, play a crucial role in signal processing and machine learning. Multiplying a vector by a full rank matrix a priori costs of the order of the number of non-zero entries in the matrix, in terms of arithmetic operations. However, matrices exist that can be applied much faster, this property being crucial to the success of certain linear transformations, such as the Fourier transform or the wavelet transform. What is the property that allows these matrices to be applied rapidly ? Is it easy to verify ? Can weapproximate matrices with ones having this property ? Can we estimate matrices having this property ? This thesis investigates these questions, exploring applications such as learning dictionaries with efficient implementations, accelerating the resolution of inverse problems or Fast Fourier Transform on graphs.Le Magoarou, LucWed, 18 Oct 2017 16:04:12 +0300http://theses.eurasip.org/theses/731/efficient-matrices-for-signal-processing-and/Estimation de la structure des morceaux de musique par analyse multicritère et contrainte de régularitéhttp://theses.eurasip.org/theses/730/estimation-de-la-structure-des-morceaux-de/Les récentes évolutions des technologies de l'information et de la communication font qu'il est aujourd'hui facile de consulter des catalogues de morceaux de musique conséquents. De nouvelles représentations et de nouveaux algorithmes doivent de ce fait être développés afin de disposer d'une vision représentative de ces catalogues et de naviguer avec agilité dans leurs contenus. Ceci nécessite une caractérisation efficace des morceaux de musique par l'intermédiaire de descriptions macroscopiques pertinentes. Dans cette thèse, nous nous focalisons sur l'estimation de la structure des morceaux de musique : il s'agit de produire pour chaque morceau une description de son organisation par une séquence de quelques dizaines de segments structurels, définis par leurs frontières (un instant de début et un instant de fin) et par une étiquette représentant leur contenu sonore.La notion de structure musicale peut correspondre à de multiples acceptions selon les ...Sargent, GabrielWed, 18 Oct 2017 11:18:52 +0300http://theses.eurasip.org/theses/730/estimation-de-la-structure-des-morceaux-de/Cosparse regularization of physics-driven inverse problemshttp://theses.eurasip.org/theses/729/cosparse-regularization-of-physics-driven-inverse/Inverse problems related to physical processes are of great importance in practically every field related to signal processing, such as tomography, acoustics, wireless communications, medical and radar imaging, to name only a few. At the same time, many of these problems are quite challenging due to their ill-posed nature. On the other hand, signals originating from physical phenomena are often governed by laws expressible through linear Partial Differential Equations (PDE), or equivalently, integral equations and the associated Green’s functions. In addition, these phenomena are usually induced by sparse singularities, appearing as sources or sinks of a vector field. In this thesis we primarily investigate the coupling of such physical laws with a prior assumption on the sparse origin of a physical process. This gives rise to a “dual” regularization concept, formulated either as sparse analysis (cosparse), yielded by a PDE ...Kitić, Srđan Wed, 18 Oct 2017 10:28:58 +0300http://theses.eurasip.org/theses/729/cosparse-regularization-of-physics-driven-inverse/Artificial Bandwidth Extension of Telephone Speech Signals Using Phonetic A Priori Knowledgehttp://theses.eurasip.org/theses/728/artificial-bandwidth-extension-of-telephone/The narrowband frequency range of telephone speech signals originally caused by former analog transmission techniques still leads to frequent acoustical limitations in today’s digital telephony systems. It provokes muffled sounding phone calls with reduced speech intelligibility and quality. By means of artificial speech bandwidth extension approaches, missing frequency components can be estimated and reconstructed. However, the artificially extended speech bandwidth typically suffers from annoying artifacts. Particularly susceptible to this are the fricatives /s/ and /z/. They can hardly be estimated based on the narrowband spectrum and are therefore easily confusable with other phonemes as well as speech pauses. This work takes advantage of phonetic a priori knowledge to optimize the performance of artificial bandwidth extension. Both the offline training part conducted in advance and the main processing part performed later on shall be thereby provided with important phoneme information. As ...Bauer, Patrick MarcelMon, 09 Oct 2017 22:47:35 +0300http://theses.eurasip.org/theses/728/artificial-bandwidth-extension-of-telephone/Epigraphical splitting of convex constraints. Application to image recovery, supervised classification, and image forgery detection.http://theses.eurasip.org/theses/727/epigraphical-splitting-of-convex-constraints/In this thesis, we present a convex optimization approach to address three problems arising in multicomponent image recovery, supervised classification, and image forgery detection. The common thread among these problems is the presence of nonlinear convex constraints difficult to handle with state-of-the-art methods. Therefore, we present a novel splitting technique to simplify the management of such constraints. Relying on this approach, we also propose some contributions that are tailored to the aforementioned applications. The first part of the thesis presents the epigraphical splitting of nonlinear convex constraints. The principle is to decompose the sublevel set of a block-separable function into a collection of epigraphs. So doing, we reduce the complexity of optimization algorithms when the above constraint involves the sum of absolute values, distance functions to a convex set, Euclidean norms, infinity norms, or max functions. We demonstrate through numerical ...Chierchia, GiovanniSun, 08 Oct 2017 17:30:56 +0300http://theses.eurasip.org/theses/727/epigraphical-splitting-of-convex-constraints/Optimal estimation of diffusion MRI parametershttp://theses.eurasip.org/theses/726/optimal-estimation-of-diffusion-mri-parameters/Diffusion magnetic resonance imaging (dMRI) is currently the method of choice for the in vivo and non-invasive quantification of water diffusion in biological tissue. Several diffusion models have been proposed to obtain quantitative diffusion parameters, which have shown to provide novel information on the structural and organizational features of biological tissue, the brain white matter in particular. The goal of this dissertation is to improve the accuracy of the diffusion parameter estimation, given the non-Gaussian nature of the diffusion-weighted MR data. In part I of this manuscript, the necessary basics of dMRI are provided. Next, Part II deals with diffusion parameter estimation and includes the main contributions of the research. Finally, Part III covers the construction of a population-based dMRI atlas of the rat brain.Veraart, JelleTue, 03 Oct 2017 00:49:27 +0300http://theses.eurasip.org/theses/726/optimal-estimation-of-diffusion-mri-parameters/Towards In Loco X-ray Computed Tomographyhttp://theses.eurasip.org/theses/724/towards-in-loco-x-ray-computed-tomography/Computed tomography (CT) is a non-invasive imaging technique that allows to reveal the inner structure of an object by combining a series of projection images that were acquired from dierent directions. CT nowadays has a broad range of applications, including those in medicine, preclinical research, nondestructive testing, materials science, etc. One common feature of the tomographic setups used in most applications is the requirement to put an object into a scanner. The rst major disadvantage of such a requirement is the constraint imposed on the size of the object that can be scanned. The second one is the need to move the object which might be di cult or might cause undesirable changes in the object. A possibility to perform in loco, i. e. on site, tomography will open up numerous applications for tomography in nondestructive testing, security, medicine, archaeology ...Dabravolski, AndreiTue, 03 Oct 2017 00:44:34 +0300http://theses.eurasip.org/theses/724/towards-in-loco-x-ray-computed-tomography/Local Prior Knowledge in Tomographyhttp://theses.eurasip.org/theses/723/local-prior-knowledge-in-tomography/Computed tomography (CT) is a technique that uses computation to form an image of the inside of an object or person, by combining projections of that object or person. The word tomography is derived from the Greek word tomos, meaning slice. The basis for computed tomography was laid in 1917 by Johann Radon, an Austrian mathematician. Computed tomography has a broad range of applications, the best known being medical imaging (the CT scanner), where X-rays are used for making the projection images. The rst practical application of CT was, however, in astronomy, by Ronald Bracewell in 1956. He used CT to improve the resolution of radio-astronomical observations. The practical applications in this thesis are from electron tomography, where the images are made with an electron microscope, and from preclinical research, where the images are made with a CT scanner. There ...Roelandts, TomTue, 03 Oct 2017 00:41:45 +0300http://theses.eurasip.org/theses/723/local-prior-knowledge-in-tomography/