Sökning: "dérive drift"

Visar resultat 11 - 15 av 18 avhandlingar innehållade orden dérive drift.

1. 11. Ruin probabilities and first passage times for self-similar processes

   Författare :Zbigniew Michna; Matematisk statistik; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Simulation of Ruin Probability; Monte Carlo Method; Skorokhod Topology; Weak Convergence; Rice s Formula; Fluid Model; Risk Model; Scaled Brownian Motion; Long Range Dependence; Fractional Brownian Motion; Renewal Process; Levy Motion; Stable Process; Self-Similar Process; Gaussian Process; Ruin Probability; First Passage Time; Exponential Bound; Picands Constant.; Mathematics; Matematik;

   Sammanfattning : This thesis investigates ruin probabilities and first passage times for self-similar processes. We propose self-similar processes as a risk model with claims appearing in good and bad periods. Then, in particular, we get the fractional Brownian motion with drift as a limit risk process. LÄS MER

3. 12. Testing the unit root hypothesis in nonlinear time series and panel models

   Författare :Rickard Sandberg; Handelshögskolan i Stockholm; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES;

   Sammanfattning : The thesis contains the four chapters: Testing parameter constancy in unit root autoregressive models against continuous change; Dickey-Fuller type of tests against nonlinear dynamic models; Inference for unit roots in a panel smooth transition autoregressive model where the time dimension is fixed; Testing unit roots in nonlinear dynamic heterogeneous panels. In Chapter 1 we derive tests for parameter constancy when the data generating process is non-stationary against the hypothesis that the parameters of the model change smoothly over time. LÄS MER

4. 13. Modelling and Simulation of Turbulent Gas-Solid Flows applied to Fluidization

   Författare :Eric Peirano; Chalmers tekniska högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Eulerian models; fluidization; two-fluid model; two-phase flow; granular flow theory; turbulence; fluidized beds; gas-solid flows;

   Sammanfattning : Modelling of gas-solid suspensions has been studied with emphasis on suitable closure laws. A study of characteristic time scales and energy dissipation mechanisms is made for the case of a simple shear flow. Applications of the modelling are presented in the form of simulation and validation of experiments in fluidized beds. LÄS MER

5. 14. RF Energy Harvesting for Zero-Energy Devices and Reconfigurable Intelligent Surfaces

   Författare :Morteza Tavana; Emil Björnson; Jens Zander; George Alexandropoulos; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Electronic waste; energy harvesting; Internet of Things; optimization; phased array; reconfigurable intelligent surfaces; stochastic geometry; wireless power transfer; wireless sensor networks; zero-energy devices.; Elektronikskrot; energiutvinning; sakernas internet; optimering; fasstyrda antenner; omkonfigurerbara intelligenta ytor; stokastisk geometri; trådlös kraftöverföring; trådlösa sensornätverk; nollenergienheter.; Informations- och kommunikationsteknik; Information and Communication Technology;

   Sammanfattning : The growth of Internet of Things (IoT) networks has made battery replacement in IoT devices increasingly challenging. This issue is particularly pronounced in scenarios with a large number of IoT devices, in locations where IoT devices are difficult to access, or when frequent replacement is necessary. LÄS MER

7. 15. Systematic Data-Driven Continual Self-Learning

   Författare :Diarmuid Corcoran; Magnus Boman; Steven Latré; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Data-Driven Methods; Self-Learning Systems; Reinforcement Learning Algorithms; Implementation Architectures; Datadrivna metoder; Självlärande system; Reinforcement Learning-algoritmer; Implementeringsarkitekturer;

   Sammanfattning : There is a lot of unexploited potential in using data-driven and self-learning methods to dramatically improve automatic decision-making and control in complex industrial systems. So far, and on a relatively small scale, these methods have demonstrated some potential to achieve performance gains for the automated tuning of complex distributed systems. LÄS MER