5 papers · 1 filter
Integrated Gaussian Processes for Robust and Adaptive Multi-Object Tracking
Fred Lydeard, Bashar I. Ahmad, Simon Godsill
This paper presents a computationally efficient multi-object tracking approach that can minimise track breaks (e.g., in challenging environments and against agile targets), learn t…
Distributed Expectation Propagation for Multi-Object Tracking over Sensor Networks
Qing Li, Runze Gan, James R. Hopgood +2
In this paper, we present a novel distributed expectation propagation algorithm for multiple sensors, multiple objects tracking in cluttered environments. The proposed framework en…
State Space Model Programming in Turing.jl
Tim Hargreaves, Qing Li, Charles Knipp +3
State space models (SSMs) are a powerful and widely-used class of probabilistic models for analysing time-series data across various fields, from econometrics to robotics. Despite…
Bayesian Non-Parametric Inference for Lévy Measures in State-Space Models
Bill Z. Lin, Simon Godsill
Lévy processes, known for their ability to model complex dynamics with skewness, heavy tails, and discontinuities, play a critical role in stochastic modeling across various domain…
RIFT: Entropy-Optimised Fractional Wavelet Constellations for Ideal Time-Frequency Estimation
James M. Cozens, Simon J. Godsill
We introduce a new method for estimating the Ideal Time-Frequency Representation (ITFR) of complex nonstationary signals. The Reconstructive Ideal Fractional Transform (RIFT) compu…