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Optimal-Online-Nonlinear-Non-Gaussian-State-Estimation

Written by Hang Zhong Introductions about the codes:

You can run the following main program for tasks: 'task_main.m' is for task 1 'EKFandIEKF_main.m' is for Kalman filter and Iterated Kalman filter for task2,3,4 'GDandGDRP_main.m' is for grid based method and improved grid based method for task2,3,4 'SIRandASIR_main.m' is for SIR particle filter and ASIR particle filter for task2,3,4

functions: 'State_updt.m' and 'Output_pred.m' are the state space model functions 'State_der.m' and 'Output_der.m' are the derivatives of state space model functions 'MTCL.m' is using Monte Carlo simulations to get the state distributions 'EKF.m' is extended Kalman filter algorithm 'IEKF.m' is iterated extended Kalman filter algorithm 'GD.m' and 'MAPGD.m' are grid based method 'GDRP.m' is improved grid based method 'SIR.m' is SIR particle filter algorithm 'ASIR.m' is ASIR particle filter algorithm

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