Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"Sparse Modeling"”.
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Sparse Modeling of Grouped Line Spectra
… of the model orders, this thesis exploits sparse modeling, where the orders are implicitly chosen. For line spectra, the non-linear parametric model is approximated by a linear system, containing an overcomplete basis of candidate frequencies, called a dictionary, and a large set of linear …
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LOW RANK AND SPARSE MODELING FOR DATA ANALYSIS
… learning and data mining tasks. Low-rank and sparse modeling are emerging mathematical tools dealing with uncertainties of real-world data. Leveraging on the underlying structure of data, low-rank and sparse modeling approaches have achieved impressive performance in many data analysis tasks. …
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Sparse modeling of high-dimensional data for learning and vision
Sparse representations account for most or all of the information of a signal by a linear combination of a few elementary signals called atoms, and have increasingly become recognized as providing high performance for applications as diverse as noise reduction, compression, inpainting, compressive …
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Sparsity and robustness in modern statistical estimation
… of modern machine learning and statistics are sparse modeling and robustness. Sparse modeling enables the construction of simpler statistical models, with examples including the Lasso and matrix completion. At the same time, statistical models need to be robust--they should perform well when …
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Exploiting spatial and spectral information for audio source separation and speaker diarization
… the adoption of probabilistic and advanced modeling aims at exploiting the diversity of multichannel propagation, and the redundancy of source signals. Moreover, prior information about the environments or the signals is helpful to improve the quality and to accelerate the separation. In …
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A subspace approach to accelerated cardiovascular magnetic resonance imaging
… imaging approach comprises developments in image modeling, data acquisition, and image reconstruction. A spatiotemporal image model is designed to represent the particular subspace structure of cardiovascular images. The data acquisition development is composed of: a) a sampling strategy which …
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Sparsity in Machine Learning: Theory and Applications
… It offers a rigorous framework to build sparse models and has proved to provide more accurate and sparse models than other approaches including the ones using sparsity-inducing regularization norms. This thesis focuses on the application of integer optimization to address sparsity …
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High-resolution full-vocal-tract dynamic speech magnetic resonance imaging
… high-spatiotemporal-resolution speech MRI from sparsely sampled data is achieved by employing a low-rank imaging model that leverages the spatiotemporal correlations in dynamic speech motion; (b) a self-navigated sampling strategy is developed and employed to acquire spatiotemporal data at high …
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l0 Sparse signal processing and model selection with applications
Sparse signal processing has far-reaching applications including compressed sensing, media compression/denoising/deblurring, microarray analysis and medical imaging. The main reason for its popularity is that many signals have a sparse representation given that the basis is suitably selected. …
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Adaptive MIMO Radar for Target Detection, Estimation, and Tracking
We develop and analyze signal processing algorithms to detect, estimate, and track targets using multiple-input multiple-output: MIMO) radar systems. MIMO radar systems have attracted much attention in the recent past due to the additional degrees of freedom they offer. They are commonly used in …
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Adaptive nonlocal and structured sparse signal modeling and applications
"Features based on sparse representation, especially using the synthesis dictionary model, have been heavily exploited in signal processing and computer vision. Many applications such as image and video denoising, inpainting, demosaicing, super-resolution, magnetic resonance imaging (MRI), and …