The analysis of chaotic time-series data

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


This paper presents a brief survey of time-series analysis methods that are applicable to processes whose behavior can be described as low-dimensional chaos. The goal of these methods is to allow experimentalists to obtain local estimates of the dynamics directly from a set of data. These estimates are often sufficiently accurate to attempt noise reduction, prediction, and control.

Original languageEnglish (US)
Pages (from-to)313-319
Number of pages7
JournalSystems and Control Letters
Issue number5
StatePublished - Oct 10 1997


  • Chaotic dynamics
  • Embedding
  • Time series

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)
  • Mechanical Engineering
  • Electrical and Electronic Engineering


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