Surrogate test for noise-contaminated dynamics in the Duffing oscillator

To identify random signals from nonlinear system under stochastic background is very difficult, and standard dynamical methods are generally not applicable. The pseudo-periodic surrogate algorithm recently developed by Small is introduced to test the sample time series in the Duffing oscillator under the Gaussian white noise excitation. The correlation dimensions of the noisy periodic, noise-induced chaotic and random-dominant responses of the system are compared with their corresponding artificial data respectively. Meanwhile, the leading Lyapunov exponents by Rosenstein's algorithm are also presented to validate the identification idea on the system's sample time series.