Detecting subthreshold events in noisy data by symbolic dynamics |
| |
Authors: | Beim Graben Peter Kurths Jürgen |
| |
Affiliation: | Institute of Linguistics, Universit?t Potsdam, P.O. Box 601553, 14415 Potsdam, Germany. peter@ling.uni-potsdam.de |
| |
Abstract: | We show that a symmetric threshold crossing detector can be described by a symbolic dynamics of a static three-symbol encoding which is highly efficient to detect subthreshold events in noisy nonstationary data. After computing instantaneous word statistics and running cylinder entropies, we introduce a mean-field transformation of the three-symbol dynamics considered as a Potts-spin lattice onto a distribution of two symbols. This transformed word statistics enables one to derive an estimator of the signal-to-noise ratio (SNR). Subthreshold events are then proven by a prominent peak of the SNR estimator as a function of the noise intensity. |
| |
Keywords: | |
本文献已被 PubMed 等数据库收录! |
|