Sökning: "MAP estimation"
Visar resultat 1 - 5 av 95 avhandlingar innehållade orden MAP estimation.
1. Model Selection and Sparse Modeling
Sammanfattning : Parametric signal models are used in a multitude of signal processing applications. This thesis deals with signals for which there are many candidate models, and it is not a priori known which model is the most appropriate one. LÄS MER
2. Estimation and Detection with Applications to Navigation
Sammanfattning : The ability to navigate in an unknown environment is an enabler for truly utonomous systems. Such a system must be aware of its relative position to the surroundings using sensor measurements. It is instrumental that these measurements are monitored for disturbances and faults. LÄS MER
3. Studies in plausibility theory, with applications to physics
Sammanfattning : The discipline usually called `probability theory' can be seen as the theory which describes and sets standard norms to the way we reason about plausibility. From this point of view, this `plausibility theory' is a province of logic, and the following informal proportion subsists: plausibility theory is to the common notion of `plausibility', as deductive logic is to the common notion of `truth'. LÄS MER
4. Distributed Road Grade Estimation for Heavy Duty Vehicles
Sammanfattning : An increasing need for goods and passenger transportation drives continued worldwide growth in traffic. As traffic increases environmental concerns, traffic safety, and cost efficiency become ever more important. Advancements in microelectronics open the possibility to address these issues through new advanced driver assistance systems. LÄS MER
5. Applications in Monocular Computer Vision using Geometry and Learning : Map Merging, 3D Reconstruction and Detection of Geometric Primitives
Sammanfattning : As the dream of autonomous vehicles moving around in our world comes closer, the problem of robust localization and mapping is essential to solve. In this inherently structured and geometric problem we also want the agents to learn from experience in a data driven fashion. LÄS MER
