EXPLORING SHARED RISKS THROUGH PUBLIC-PRIVATE PARTNERSHIPS IN PUBLIC HEALTH PROGRAMS: A MIXED METHOD


Non-Gaussian Filters for Nonlinear Continuous-Discrete Models

In this paper, we propose using an Clutch Component ensemble Kalman filter (EnKF) and particle filters (PFs) to obtain superior state estimation accuracy for nonlinear continuous-discrete models.We discretize the Ito-type stochastic differential system model by means of the usual procedure and suppress the approximation error by using small discret

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