Since the landmark work of RE Kalman in the 1960s, considerable efforts have been
devoted to time series state space models for a large variety of dynamic estimation …

From the celebrated Gaussian mixture, model averaging estimators to the cutting-edge multi-
Bernoulli mixture of various forms, finite mixture models offer a fundamental and flexible …

Since the beginning of 2020, the outbreak of a new strain of Coronavirus has caused
hundreds of thousands of deaths and put under heavy pressure the world's most advanced …

In Gilholm et al.'s extended target model, the number of measurements generated by a
target is Poisson distributed with measurement rate γ. Practical use of this extended target …

Abstract The efficiency of Monte Carlo algorithms for light transport simulation is directly
related to their ability to importance‐sample the product of the illumination and reflectance in …

We propose a particle-based distributed PHD filter for tracking the states of an unknown,
time-varying number of targets. To reduce communication, the local PHD filters at …

In most European countries, residential assets account for as much as 85% of the building
stock floor area and are, on average, very outdated and energy inefficient. Moreover, the …

In this article, we demonstrate how a variation of the joint integrated probabilistic data
association with interacting multiple models and a visibility state can be derived as a special …

Successful space domain awareness (SDA) requires maintaining track custody of
cooperative and noncooperative cislunar space objects (CSOs) through both ballistic and …

In power systems, state estimation (SE) is a widely investigated method to collate field
measurements and power flow (PF) equations to derive the most-likely state of the observed …