Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 24 for “"bayesian filtering"”.
-
Predictive parameter estimation for Bayesian filtering
… that it augments, rather than disrupts, existing filtering algorithms. I additionally present two important variants; first, I extend CELLO to learn even when ground truth vehicle states are unavailable; and second, I present an equivalent Bayesian algorithm. I then use CELLO to learn covariance …
-
Sequential bayesian filtering for spatial arrival time estimation
… for accurate estimation. We develop a particle filtering approach that treats arrival times as "targets", dynamically modeling their "location" at arrays of spatially separated receivers. Using Monte Carlo simulations, we perform an evaluation of our method and compare it to conventional Maximum …
-
Recursive Bayesian Filtering Through a Mixture of Gaussian and Discrete Particles
Conventional solutions to nonlinear filtering problems fall into two categories, deterministic and stochastic approaches. While the former is heavily used due to low computational demand, approximation error is tied to their initialization, which causes difficulty during long term application. The …
-
Towards robust inference for Bayesian filtering of linear Gaussian dynamical systems subject to additive change
… a computationally cheap solution via generalised Bayesian posteriors with a diffusion Stein divergence loss resulting in the diffusion score matching Kalman filter - a modified algorithm akin in complexity to the regular Kalman filter. For this new filter interpretations of novel terms, stability …
-
Interactive Bayesian identification of kinematic mechanisms
… formulation of this problem, using Bayesian filtering techniques to maintain a distributional estimate of the mechanism type and parameters. We begin by implementing a discrete Bayesian filter. We demonstrate the approach on a domain with four primitive and two composite mechanisms. …
-
Minimal Infrastructure Radio Frequency Home Localisation Systems
… classifiers to a Hidden Markov Model Bayesian filtering framework. New location prediction performance metrics are developed and signicant performance improvements are demonstrated with the novel extension of Hidden Markov Models to higher-order Markov movement models. With the simple …
-
An Expected Entropy Reduction (EER) Approach to Target Tracking in Maritime Environment for On-board Camera
… such that targets can be tracked utilizing the Bayesian filtering technique. A sensor planning strategy based on expected entropy reduction (EER) is developed to select optimal sensor field of view (FoV) locations such that the expected entropy reduction is maximized.
-
Probabilistic search: a Bayesian approach in a continuous workspace
… sensor. To model this problem, the widely used Bayesian filtering approach is employed to obtain the general filtering equations for the posterior distribution representing the object's location over the workspace. Given a likelihood and prior belief belonging to the exponential family class, …
-
Object tracking in mmWave radar networks
… the use of these three algorithms in addition to Bayesian filtering, MiNiMAP is capable of tracking a single object with a network of mmWave radars. Indoor localization experiments validate MiNiMAP's overall system performance and the impact of each algorithm.
-
Particle filtering for frequency estimation from acoustic time-series in dispersive media
… focuses on the development of sequential Bayesian filtering methods to obtain accurate estimates of instantaneous frequencies using Short Term Fourier Transforms within the acoustic field measured at an array of hydrophones, which can be used in a subsequent step for the estimation of …
-
Domain-Independent Mode Estimation for Human-Robot Collaboration
… activity states while integrating recursive Bayesian filtering to maintain belief under noisy observations. Unlike low-level trajectory tracking or deep-learned classifiers, qualitative spatial filtering operates at the right level of abstraction to recognize symbolic actions. It can also …
-
Robust Predictive Resource Allocation for Video Delivery Over Future Wireless Networks
… to provide real-time allocation. Moreover, Bayesian filtering methods (e.g. Kalman Filter) are adopted to continuously learn the degree of uncertainty which decreases the cost of robustness and maintains the prediction gains. Different variants for the robust framework are proposed such as …
-
Language-Guided Video Understanding with Foundation Models
… that combines Large Multimodal Models with Bayesian filtering. Finally, the thesis addresses the reliability of language model estimates over video and explores whether synthetic videos generated by text-to-video models can improve their temporal understanding without human annotation. By …
-
Multichannel source separation and tracking with phase differences by random sample consensus
… These algorithms combine directional statistics, Bayesian filtering theory, and probabilistic data association techniques to track the speakers with mixtures of directional distributions.
-
Novel probabilistic and distributed algorithms for guidance, control, and nonlinear estimation of large-scale multi-agent systems
… of heterogeneous sensing agents. The Distributed Bayesian Filtering (DBF) algorithm, the sensing agents combine their normalized likelihood functions using the logarithmic opinion pool and the discrete-time dynamic average consensus algorithm. Each agent's estimated likelihood function converges …
-
Intelligent video surveillance
… is based on rigid motion segmentation by Bayesian filtering. The Bayesian filter, which was proposed specially for this method and contributes to its novelty, is formulated as a generic approach, and then applied to the video analytics problems. The method is augmented with optional object …
-
Ensemble-based reservoir history matching using hyper-reduced-order models
… is adopted. In addition, two types of sequential Bayesian filtering for history matching are considered to investigate the performance of the developed hyper-reduced-order model to relive the associated computational cost. First, an ensemble Kalman filter (EnKF) is considered for Gaussian system …
-
Trajectory bundle estimation For perception-driven planning
… a set of trajectory bundles. We then develop a Bayesian filtering framework that enables us to estimate a belief over which trajectory bundles are feasible based on the history of actions and observations of the vehicle. We test our algorithms by using them to navigate a simulated fixed wing air …
-
Sensor Integration for Low-Cost Crash Avoidance
… A probabilistic approach was used based on Bayesian filtering with a prediction-correction algorithm. Sensor fusion was implemented using joint a probability algorithm. The output of the system is a prediction of the likelihood of the presence of a vehicle in a given region near the host …
-
A Bayesian occupancy grid filter for robust pedestrian dead reckoning
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-12-01
Page 1 of 2