Browsing Department of Computational and Data Sciences (CDS) by Subject "Fluid Dynamics"
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Theory and Algorithms for sequential non-Gaussian Bayesian filtering and estimation
Seamless integration of dynamical system models with sparse measurements, called as Data Assimilation, is important in many applications like weather forecasting, socio-economics, navigation, and beyond. In order to produce ...