Nonlinear Sciences – Chaotic Dynamics
Scientific paper
1999-09-30
Phys. Rev. E 55 (1997) 5443
Nonlinear Sciences
Chaotic Dynamics
6 pages, 2 figures
Scientific paper
10.1103/PhysRevE.55.5443
The performance of a number of different measures of nonlinearity in a time series is compared numerically. Their power to distinguish noisy chaotic data from linear stochastic surrogates is determined by Monte Carlo simulation for a number of typical data problems. The main result is that the ratings of the different measures vary from example to example. It seems therefore preferable to use an algorithm with good overall performance, that is, higher order autocorrelations or nonlinear prediction errors.
Schmitz Andreas
Schreiber Thomas
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