### Abstract

Parallel to the rapid development of nonlinear dynamics, there has been a tremendous amount of effort devoted to data analysis. Suppose an experiment is conducted and some time series are measured. Such a time series can be, for instance, a voltage signal from a physical or a biological experiment, or the concentration of a substance in a chemical reaction, or the amount of instantaneous traffic at a point in the Internet, and so on. The general question is this: what can we say about the underlying dynamical system that generates the time series if the equations governing the time evolution of the system are unknown and the only available information about the system is a set of measured time series?.

Original language | English (US) |
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Title of host publication | Applied Mathematical Sciences (Switzerland) |

Publisher | Springer |

Pages | 413-434 |

Number of pages | 22 |

DOIs | |

State | Published - Jan 1 2011 |

### Publication series

Name | Applied Mathematical Sciences (Switzerland) |
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Volume | 173 |

ISSN (Print) | 0066-5452 |

ISSN (Electronic) | 2196-968X |

### Keywords

- Chaotic Attractor
- Lyapunov Exponent
- Periodic Orbit
- Positive Lyapunov Exponent
- Topological Entropy

### ASJC Scopus subject areas

- Applied Mathematics

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## Cite this

*Applied Mathematical Sciences (Switzerland)*(pp. 413-434). (Applied Mathematical Sciences (Switzerland); Vol. 173). Springer. https://doi.org/10.1007/978-1-4419-6987-3_12