Sökning: "Markov modelling"

Visar resultat 6 - 10 av 47 uppsatser innehållade orden Markov modelling.

  1. 6. Probability Based Path Planning of Unmanned Ground Vehicles for Autonomous Surveillance : Through World Decomposition and Modelling of Target Distribution

    Master-uppsats, Linköpings universitet/Reglerteknik

    Författare :Per Liljeström; [2022]
    Nyckelord :Probability based path planning; Unmanned ground vehicles; UGV; Autonomous surveillance; Cell decomposition; Spatial partitioning; Target distribution modeling; Decay function; Last-seen function; Stochastic processes; Markov chain; Markov process; Markov planner;

    Sammanfattning : The interest in autonomous surveillance has increased due to advances in autonomous systems and sensor theory. This thesis is a preliminary study of the cooperation between UGVs and stationary sensors when monitoring a dedicated area. The primary focus is the path planning of a UGV for different initial intrusion alarms. Cell decomposition, i. LÄS MER

  3. 7. Diffusion and Camera-Noise Modelling for Analysis of Single-Particle Tracking Movies

    Master-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

    Författare :Erik Clarkson; [2022]
    Nyckelord :reaction-diffusion; camera-noise modelling; single-particle tracking; Gillespie simulations; Physics and Astronomy;

    Sammanfattning : Interactions between T-cells and other body cells is an essential part of the immune system. It involves the binding between surface receptors of the two cells. Specifically, T-cell receptors (TCRs) bind onto pMHC (peptide-loaded major histocompatibility complex) molecules on the partnering cell surface. LÄS MER

  4. 8. Towards Deep Learning Accelerated Sparse Bayesian Frequency Estimation

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Mika Persson; [2022]
    Nyckelord :Bayesian Statistics; Deep Learning; Frequency Estimation; Generative Adversarial Networks; Artificial Neural Networks; Statistical Modelling; Mathematics and Statistics;

    Sammanfattning : The Discrete Fourier Transform is the simplest way to obtain the spectrum of a discrete complex signal. This thesis concerns the case when the signal is known to contain a small (unknown) number of frequencies, not limited to the discrete Fourier frequencies, embedded in complex Gaussian noise. LÄS MER

  5. 9. Spatial Statistical Modelling of Insurance Claim Frequency

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Daniel Faller; [2022]
    Nyckelord :Insurance risk; claim frequency; Markov chain Monte Carlo MCMC ; Riemann manifold Metropolis adjusted Langevin algorithm MMALA ; spatial statistics; Gaussian Markov random field GMRF ; preconditioned Crank Nicolson Langevin algorithm pCNL ; Gibbs sampling; Bayesian hierarchical modelling; high dimensional; shrinkage prior; horseshoe prior; regularisation.; Mathematics and Statistics;

    Sammanfattning : In this thesis a fully Bayesian hierarchical model that estimates the number of aggregated insurance claims per year for non-life insurances is constructed using Markov chain Monte Carlo based inference with Riemannian Langevin diffusion. Some versions of the model incorporate a spatial effect, viewed as the relative spatial insurance risk that originates from a policyholder's geographical location and where the relative spatial insurance risk is modelled as a continuous spatial field. LÄS MER

  7. 10. Evaluation of Probabilistic Programming Frameworks

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Carl Munkby; [2022]
    Nyckelord :Computational statistics; Bayesian statistics; Probabilistic programming; Probabilistic modelling; Stan; TensorFlow Probability; Pyro; NumPyro; Markov Chain Monte Carlo; Hamiltonian Monte Carlo; NUTS;

    Sammanfattning : In recent years significant progress has been made in the area of Probabilistic Programming, contributing to a considerably easier workflow for quantitative research in many fields. However, as new Probabilistic Programming Frameworks (PPFs) are continuously being created and developed, there is a need for finding ways of evaluating and benchmarking these frameworks. LÄS MER