An On-Line Change Detection Scheme for Nonlinear Time Series Data from Unknown Dynamical Systems: A Bayesian Appraoch Using Sequential Monte Carlo

This paper attempts to perform on-line change detection given time series data from unknown nonlinear dynamical systems. In the algorithm, the probability of occurrence of an abrupt change is estimated within a Bayesian framework. The implementation is done via sequential Monte Carlo (SMC). The proposed scheme is tested against two examples with nonlinear dynamical systems