In this work, we present some examples of applications of the so-called Rao-Blackwellised Particle Filter (RBPF). RBPFs are an extension to Particle Filters (PFs) which are applic...
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, ...
A new method for instantaneous phase tracking of oscillatory signals in a narrow band frequency range is proposed. Empirical mode decomposition (EMD), as an adaptive and data-driv...
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...
Abstract. In this paper we discuss new adaptive proposal strategies for sequential Monte Carlo algorithms--also known as particle filters--relying on new criteria evaluating the qu...