This work evaluates a previously introduced algorithm called Particle-Based Rapid Incremental Smoother within the framework of state inference and parameter identiﬁcation in Jump Markov Non-Linear System. It is applied to the recursive form of two well-known Maximum Likelihood based algorithms who face the common challenge of online computation of smoothed additive functionals in order to accomplish the task of model parameter estimation. This work extends our previous contributions on identiﬁcation of Markovian switching systems with the goal to reduce the computational complexity. A benchmark problem is used to illustrate the results.
Engineering and Technology (hsv)
Electrical Engineering, Electronic Engineering, Information Engineering (hsv)