4 papers
Input design for Bayesian identification of non-linear state-space models
Aditya Tulsyan, Swanand R. Khare, Biao Huang +2
We propose an algorithm for designing optimal inputs for on-line Bayesian identification of stochastic non-linear state-space models. The proposed method relies on minimization of…
Error analysis in Bayesian identification of non-linear state-space models
Aditya Tulsyan, Biao Huang, R. Bhushan Gopaluni +1
In the last two decades, several methods based on sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC) have been proposed for Bayesian identification of stochastic non-…
On-line Bayesian parameter estimation in general non-linear state-space models: A tutorial and new results
Aditya Tulsyan, Biao Huang, R. Bhushan Gopaluni +1
On-line estimation plays an important role in process control and monitoring. Obtaining a theoretical solution to the simultaneous state-parameter estimation problem for non-linear…
A particle filter approach to approximate posterior Cramér-Rao lower bound
Aditya Tulsyan, Biao Huang, R. Bhushan Gopaluni +1
The posterior Cramér-Rao lower bound (PCRLB) derived in Tichavský et al., 1998, provides a bound on the mean square error (MSE) obtained with any non-linear state filter. Computing…