Sökning: "Compressive Sampling"
Visar resultat 1 - 5 av 6 avhandlingar innehållade orden Compressive Sampling.
1. Cooperative Compressive Sampling
Sammanfattning : Compressed Sampling (CS) is a promising technique capable of acquiring and processing data of large sizes efficiently. The CS technique exploits the inherent sparsity present in most real-world signals to achieve this feat. Most real-world signals, for example, sound, image, physical phenomenon etc., are compressible or sparse in nature. LÄS MER
2. Mechanical properties of excavated sulfur rich soil stabilized with cement - A laboratory and field experiment
Sammanfattning : Sulfide soils are silty soils, often found in saturated conditions, under the groundwater level. Characteristics of these soils, including particle size distribution and consistency limits along with chemical composition and environmental properties, cause excavation to be necessary for construction purposes. LÄS MER
3. On Invertibility of the Radon Transform and Compressive Sensing
Sammanfattning : This thesis contains three articles. The first two concern inversion andlocal injectivity of the weighted Radon transform in the plane. The thirdpaper concerns two of the key results from compressive sensing.In Paper A we prove an identity involving three singular double integrals. LÄS MER
4. Ultra Wideband: Communication and Localization
Sammanfattning : The first part of this thesis develops methods for UWB communication. To meet the stringent regulatory body constraints, the physical layer signaling technique of the UWB transceiver should be optimally designed. LÄS MER
5. Enhanced block sparse signal recovery and bayesian hierarchical models with applications
Sammanfattning : This thesis is carried out within two projects ‘Statistical modelling and intelligentdata sampling in Magnetic resonance imaging (MRI) and positron-emission tomography(PET) measurements for cancer therapy assessment’ and ‘WindCoE -Nordic Wind Energy Center’ during my PhD study. It mainly focuses on applicationsof Bayesian hierarchical models (BHMs) and theoretical developments ofcompressive sensing (CS). LÄS MER