Sökning: "non-linear time"
Visar resultat 1 - 5 av 282 uppsatser innehållade orden non-linear time.
1. Ensuring safe docking maneuvers on floating platform using Nonlinear Model Predictive Control (NMPC)
Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : Docking maneuvers are a relevant part of the modern space mission, requiring precision and safety to ensure the success of the overall mission. This thesis proposes using a non-linear Model Predictive Control (MPC) as a controller with various constraints to ensure safe docking maneuvers for a satellite. LÄS MER
2. Quantum Optical Description of High-order Harmonic Generation
Master-uppsats, Lunds universitet/Atomfysik; Lunds universitet/Fysiska institutionenSammanfattning : High-order Harmonic Generation (HHG) is a highly non-linear process in which an atom interacts with a strong laser field. The laser field lowers the atomic potential barrier allowing bound electrons to escape into the continuum through tunnel ionization, propagate, and, with some probability, recombine with the parent ion. LÄS MER
3. Mellanrum: Towards an Entangled Audiovisual Practice
Master-uppsats, Göteborgs universitet/Högskolan för scen och musikSammanfattning : This artistic research project is a document of an entangled audiovisual practice in progress. With a generative approach and thinking in systems applied to modular synthesizers and procedural computer graphics the aim is to blur the line between the process of generating sounding material and the process of generating visual material. LÄS MER
4. Primary Drivers of Sea Level Variability in the North – Baltic Sea Transition Using Machine Learning
Master-uppsats, Göteborgs universitet/Institutionen för geovetenskaperSammanfattning : Global mean sea level is rising, however not uniformly. Regional deviations of sea surface height (SSH) are common due to local drivers, including surface winds, ocean density stratifications, vertical land- & crustal movements and more. LÄS MER
5. Kernel Methods for Regression
Kandidat-uppsats, Linnéuniversitetet/Institutionen för matematik (MA)Sammanfattning : Kernel methods are a well-studied approach for addressing regression problems by implicitly mapping input variables into possibly infinite-dimensional feature spaces, particularly in cases where standard linear regression fails to capture non-linear relationships in data. Therefore, the choice between standard linear regression and kernel regression can be seen as a tradeoff between constraints on the number of features and the number of training samples. LÄS MER