Milan Palus
Institute of Computer Science,
Academy of Sciences of the Czech Republic
Pod vodárenskou vezí 2,
182 07 Prague 8, Czech Republic
E-mail: mp@uivt.cas.cz, mp@santafe.edu
A technique for identification and quantification of chaotic dynamics in experimental time series is presented. It is based on evaluation of redundancies, information-theoretic functionals which, estimated from data generated by a chaotic dynamical system, have specific properties reflecting positive information production rate. This rate, measured by metric (Kolmogorov-Sinai) entropy, can be directly estimated from the redundancies.