Sökning: "relaxation methods"
Visar resultat 1 - 5 av 249 avhandlingar innehållade orden relaxation methods.
1. Water and protein solutions studied by field-dependent magnetic relaxation
Sammanfattning : In the work presented, nuclear magnetic resonance (NMR) relaxation is used to study wide range of systems. The thesis concerns solvent interactions studied with relaxation techniques that involve measurements at many fields, which allows the separation of individual relaxation mechanisms. LÄS MER
2. Algebraic Reconstruction Methods
Sammanfattning : Ill-posed sets of linear equations typically arise when discretizing certain types of integral transforms. A well known example is image reconstruction, which can be modeled using the Radon transform. After expanding the solution into a finite series of basis functions a large, sparse and ill-conditioned linear system occurs. LÄS MER
3. Zero-Field Splitting in Gd(III) complexes : Towards a molecular understanding of paramagnetic relaxation
Sammanfattning : The prime objectives of contrast agents in Magnetic Resonance Imaging(MRI) is to accelerate the relaxation rate of the solvent water protons in the surrounding tissue. Paramagnetic relaxation originates from dipole-dipole interactions between the nuclear spins and the fluctuating magnetic field induced by unpaired electrons. LÄS MER
4. Conditional Subgradient Methods and Ergodic Convergence in Nonsmooth Optimization
Sammanfattning : The topic of the thesis is subgradient optimization methods in convex, nonsmooth optimization. These methods are frequently used, especially in the context of Lagrangean relaxation of large scale mathematical programs where they are remarkably often able to quickly identify near-optimal Lagrangean dual solutions. LÄS MER
5. Initialization Methods for System Identification
Sammanfattning : In the system identification community a popular framework for the problem of estimating a parametrized model structure given a sequence of input and output pairs is given by the prediction-error method. This method tries to find the parameters which maximize the prediction capability of the corresponding model via the minimization of some chosen cost function that depends on the prediction error. LÄS MER