Numerical Studies in Nonlinear Filtering

Inhalt
Preliminaries.- Estimation of parameters via state observation.- Filtering via Markov chains approximation.- A Kalman filter for a class of nonlinear stochastic systems.- Approximating filters for continuous-time systems with interrupted observations.- Estimation in a multitarget environment.- State and parameter estimation.- State estimation for systems driven by wiener and poisson processes.- Prediction via Markov chains approximation.- Some extensions of linear filtering.