A Local Particle Filter Using Gamma Test Theory for High-Dimensional State Spaces

Particle filters are non-Gaussian filters, which means that the assumption that the error distribution of the ensemble should be Gaussian is unnecessary. Like the ensemble Kalman filter, particle filters are based on the Monte Carlo approximation to represent the distribution of model states. It requires a substantial number of particles to...

A particle filter-based data assimilation framework for discrete event simulations

With the advent of new sensor technologies and communication solutions, the availability of data for discrete event systems has greatly increased. This motivates research on data assimilation for discrete event simulations that has not yet fully matured. This paper presents a particle filter-based data assimilation framework for discrete event...