A Gaussian kernel based method for reducing the noise bias in estimates of correlation dimension and K2 entropy of dynamical system attractors is presented. The method is local in scale space and requires for each scale, only the knowledge of the function △. The performance of the method is demonstrated for various examples using data from the Hénon map and the Lorenz and Rôssler system.
|Journal||Physical Review E - Statistical, Nonlinear, and Soft Matter Physics|
|Issue number||1 II|
|Publication status||Published - 2001 Jul|
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- Statistics and Probability
- Condensed Matter Physics