Convergence of Regularized Particle Filters for Stochastic Reaction Networks
Convergence of Regularized Particle Filters for Stochastic Reaction Networks
Filtering for stochastic reaction networks (SRNs) is an important problem in systems/synthetic biology aiming to estimate the state of unobserved chemical species. A good solution to it can provide scientists valuable information about the hidden dynamic state and enable optimal feedback control. Usually, the model parameters need to be inferred …