title: Chaos or noise: difficulties of a distinction
abstract: In experiments, the dynamical behavior of systems is reflected in time series. Due to the finiteness of the observational data set, it is not possible to reconstruct the invariant measure up to an arbitrarily fine resolution and an arbitrarily high embedding dimension. These restrictions limit our ability to distinguish between signals generated by different systems, such as regular, chaotic, or stochastic ones, when analyzed from a time series point of view. We propose to classify the signal behavior, without referring to any specific model, as stochastic or deterministic on a certain scale of the resolution epsilon, according to the dependence of the (epsilon,tau) entropy, h(epsilon, tau), and the finite size Lyapunov exponent lambda(epsilon) on epsilon.
authors.affiliation: Dipartimento di Fisica, Universita di Roma "La Sapienza" and INFM, Unita di Roma, Piazzale Aldo Moro 2, I-00185 Roma, Italy and Max-Planck-Institut fur Physik komplexer Systeme, Nothnitzer Strasse 38, D-01187 Dresden, Germany.
authors.initials: M
authors.lastname: Cencini
authors.initials: M
authors.lastname: Falcioni
authors.initials: E
authors.lastname: Olbrich
authors.initials: H
authors.lastname: Kantz
authors.initials: A
authors.lastname: Vulpiani