Search for dissertations about: "audio localization"
Showing result 1 - 5 of 7 swedish dissertations containing the words audio localization.
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1. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing
Abstract : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. READ MORE
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2. Computer Vision without Vision : Methods and Applications of Radio and Audio Based SLAM
Abstract : The central problem of this thesis is estimating receiver-sender node positions from measured receiver-sender distances or equivalent measurements. This problem arises in many applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using ultra-wideband and mapping and positioning using round-trip-time measurements between mobile phones and Wi-Fi-units. READ MORE
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3. Infrastructure-free pedestrian localization
Abstract : Knowledge of your own and other's positions are frequently a prerequisite for acting, leading others, and interacting in and with the environment; to retrieve relevant information and to process and interpret it; and to understand, compile, and learn from observations of the surrounding and its dynamics. This holds for humans as well as for machines and systems made for supporting and controlling them. READ MORE
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4. Exploiting Sparse Structures in Source Localization and Tracking
Abstract : This thesis deals with the modeling of structured signals under different sparsity constraints. Many phenomena exhibit an inherent structure that may be exploited when setting up models, examples include audio waves, radar, sonar, and image objects. READ MORE
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5. Sparse Modeling Heuristics for Parameter Estimation - Applications in Statistical Signal Processing
Abstract : This thesis examines sparse statistical modeling on a range of applications in audio modeling, audio localizations, DNA sequencing, and spectroscopy. In the examined cases, the resulting estimation problems are computationally cumbersome, both as one often suffers from a lack of model order knowledge for this form of problems, but also due to the high dimensionality of the parameter spaces, which typically also yield optimization problems with numerous local minima. READ MORE