Improved false nearest neighbor method to detect determinism in time series data

The false nearest neighbor method introduced by Kennel et al.. [Phys. Rev. A 45, 3403 (1992)] is revisited and modified in order to ensure a correct d istinction between low-dimensional chaotic data and noise. Still, correlate d noise processes can yield vanishing percentages of false nearest neighbor s for rather low embedding dimensions and can be mistaken for deterministic signals. Therefore, the false nearest neighbors method has always to be co mbined with a surrogate data test. [S1063-651X(99)08510-4].