Sökning: "sequential importance resampling"

Hittade 4 uppsatser innehållade orden sequential importance resampling.

  1. 1. KL/TV Reshuffling : Statistical Distance Based Offspring Selection in SMC Methods

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Oskar Kviman; [2022]
    Nyckelord :;

    Sammanfattning : Over the years sequential Monte Carlo (SMC), and, equivalently, particle filter (PF) theory has enjoyed much attention from researchers. However, the intensity of developing innovative resampling methods, also known as offspring selection methods, has long been declining, with most of the popular schemes aging back two decades. LÄS MER

  3. 2. Vehicle Collision Risk Prediction Using a Dynamic Bayesian Network

    Master-uppsats, KTH/Matematisk statistik

    Författare :Jonas Lindberg; Isak Wolfert Källman; [2020]
    Nyckelord :Collision risk prediction; dynamic Bayesian network; sequential importance resampling; autonomous vehicles; ADAS; intelligent driver model; Förutsägelse av kollisionsrisk; dynamiskt Bayesianskt nätverk; sekventiell vägd simulering; autonoma fordon; ADAS; intelligent förarmodell;

    Sammanfattning : This thesis tackles the problem of predicting the collision risk for vehicles driving in complex traffic scenes for a few seconds into the future. The method is based on previous research using dynamic Bayesian networks to represent the state of the system. LÄS MER

  4. 3. Parallel Hardware for Sampling Based Nonlinear Filters in FPGAs

    Master-uppsats, Linköpings universitet/Elektroniksystem; Linköpings universitet/Tekniska högskolan

    Författare :Rakesh Kota Rajasekhar; [2014]
    Nyckelord :Particle filters; Sampling Importance Resampling Filter; Hardware architectures; Bearings-only tracking.;

    Sammanfattning : Particle filters are a class of sequential Monte-Carlo methods which are used commonly when estimating various unknowns of the time-varying signals presented in real time, especially when dealing with nonlinearity and non-Gaussianity in BOT applications. This thesis work is designed to perform one such estimate involving tracking a person using the road information available from an IR surveillance video. LÄS MER

  5. 4. Particle Methods for Indoor Tracking in WiFi Networks

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Vilhelm von Ehrenheim; [2013]
    Nyckelord :Mathematics and Statistics;

    Sammanfattning : This thesis treats the problem of positioning in WiFi networks and proposes a solution using hidden Markov models and particle lters based on sequential importance sampling with resampling. Hidden Markov models prove to be a powerful framework for this type of problem exhibiting both an intuitive and adaptive model structure. LÄS MER