ESTIMATION OF POSTERIOR PROBABILITY DENSITY DISTRIBUTIONS BY SOME FILTERING ALGORITHMS FOR OBSERVATION UPDATE

[1]  A. Stordal,et al.  Bridging the ensemble Kalman filter and particle filters: the adaptive Gaussian mixture filter , 2011 .

[2]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[3]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[4]  James L. Beck,et al.  A Bayesian probabilistic approach to structural health monitoring , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[5]  T. Higuchi,et al.  Merging particle filter for sequential data assimilation , 2007 .

[6]  Iason Papaioannou,et al.  Bayesian Updating with Structural Reliability Methods , 2015 .

[7]  Geir Evensen,et al.  The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .

[8]  G. Kitagawa Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models , 1996 .

[9]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[10]  J. Beck,et al.  Bayesian Updating of Structural Models and Reliability using Markov Chain Monte Carlo Simulation , 2002 .

[11]  Peter Jan,et al.  Particle Filtering in Geophysical Systems , 2009 .

[12]  A. Budhiraja,et al.  Modified particle filter methods for assimilating Lagrangian data into a point-vortex model , 2008 .

[13]  N. Gordon,et al.  Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .

[14]  M. Pitt,et al.  Filtering via Simulation: Auxiliary Particle Filters , 1999 .