Particle filtering (PF) for dynamic Bayesian networks (DBNs) with discrete-state spaces includes a resampling step which concentrates samples according to their relative weight in ...
Wildfire propagation is a complex process influenced by many factors. Simulation models of wildfire spread, such as DEVS-FIRE, are important tools for studying fire behavior. This...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
— Location tracking in wireless networks has many applications, including enhanced network performance. In this work we investigate the experimental use of “particle filter”...