Estimating system parameters from chaotic time series with synchronization optimized by a genetic algorithm.

A method is proposed to estimate system parameters by optimizing synchronization with a genetic algorithm. This method can effectively find the parameter values of a chaotic system with a rugged parameter landscape. Furthermore, even the parameters of a 200-dimensional coupled-map-lattice spatiotemporal chaotic system can be extracted from a scalar time series. Finally, a Chua's circuit experiment shows the capacity of this method to estimate multiple parameters of real systems.