Separation of stochastic and deterministic information from seismological time series with nonlinear dynamics and maximum entropy methods

Rafael M. Gutiérrez, Gina M. Useche, Elias Buitrago

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a procedure developed to detect stochastic and deterministic information contained in empirical time series, useful to characterize and make models of different aspects of complex phenomena represented by such data. This procedure is applied to a seismological time series to obtain new information to study and understand geological phenomena. We use concepts and methods from nonlinear dynamics and maximum entropy. The mentioned method allows an optimal analysis of the available information.

Original languageEnglish (US)
Title of host publicationBayesian Inference and Maximum Entropy Methods in Science and Engineering - 27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2007
Pages410-417
Number of pages8
DOIs
StatePublished - 2007
Event27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2007 - Saratoga Springs, NY, United States
Duration: Jul 8 2007Jul 13 2007

Publication series

NameAIP Conference Proceedings
Volume954
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2007
CountryUnited States
CitySaratoga Springs, NY
Period7/8/077/13/07

Keywords

  • Maximum entropy
  • Nonlinear dynamics
  • Seismology
  • Separation problem
  • Time series

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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