• Corpus ID: 246063838

Sequential Bayesian Inference for Uncertain Nonlinear Dynamic Systems: A Tutorial

  title={Sequential Bayesian Inference for Uncertain Nonlinear Dynamic Systems: A Tutorial},
  author={Konstantinos E. Tatsis and Vasilis K. Dertimanis and Eleni N. Chatzi},
In this article, an overview of Bayesian methods for sequential simulation from posterior distributions of nonlinear and non-Gaussian dynamic systems is presented. The focus is mainly laid on sequential Monte Carlo methods, which are based on particle representations of probability densities and can be seamlessly generalized to any state-space representation. Within this context, a unified framework of the various Particle Filter (PF) alternatives is presented for the solution of state, state… 
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