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.
Results
Showing 1 to 8 of 8 for “"sparse model"”.
-
Fast MRI with sparse sampling: models, algorithms, and applications
… This research addresses such a problem from a sparse sampling perspective. We have proposed novel constrained imaging approaches, including imaging models and reconstruction algorithms, to enable high-quality reconstruction from highly undersampled data. The utility of the proposed techniques …
-
A Joint Dictionary-Based Single-Image Super-Resolution Model
… for the practical applications. Our proposed model, which is known as Joint Dictionary-based Super-Resolution (JDSR) algorithm, is a new sparsity-based super-resolution approach. Based on the observation that the initial values of Non-locally Centralized Sparse Representation (NCSR) model will …
-
Seismic Data Conditioning and Inversion with Bayesian Methods and Dynamic Time-Warping
… The Normal-Jeffreys prior computes a sparse model that estimates observational noise variance which regularizes the solution. Moreover, Amplitude variation with offset (AVO) processing workflows are carefully designed to preserve relative amplitude between offset gathers in preparation …
-
Machine learning for applications in chemical and biological engineering
… there is only a limited dataset available for modeling. To tackle this issue, Monte Carlo sampling was used in conjunction with an elastic net approach to subset selection. The second case study is also within the biological domain but considers a discrete outcome. The proposed algorithm …
-
Discrete and Continuous Sparse Recovery Methods and Their Applications
… we focus on the synthesis and analysis models of sparse recovery. This dissertation comprises two major topics. For the first topic, we discuss the synthesis model of sparse recovery and consider the dictionary mismatches in the model. We further introduce a continuous sparse recovery to …
-
Transform learning based image and video processing
In recent years, sparse signal modeling, especially using the synthesis dictionary model, has received much attention. Sparse coding in the synthesis model is, however, NP-hard. Various methods have been proposed to learn such synthesis dictionaries from data. Numerous applications such as image …
-
Multiple-Target Tracking in Complex Scenarios
… we develop measurement and state-space models, and then exploit the structure in these models to propose efficient tracking algorithms. In addition, we address design issues such as sensor selection and resource allocation.</p><p>First, we consider MTT when the targets themselves are …
-
Efficient Distributed and Multi-Modal Machine Learning in Wireless Networks
… layer. However, training and deploying ML models in wireless networks presents two key challenges pertaining to the limited computing and resources of wireless devices and systems, and the scarce and private nature of wireless data. First, ML models at the application layer, e.g., on-device …