Symbolic dynamic analysis of complex systems for anomaly detection

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Abstract

This paper presents a novel concept of anomaly detection in complex dynamical systems using tools of Symbolic Dynamics, Finite State Automata, and Pattern Recognition, where time-series data of the observed variables on the fast time-scale are analyzed at slow time-scale epochs for early detection of (possible) anomalies. The concept of anomaly detection in dynamical systems is elucidated based on experimental data that have been generated from an active electronic circuit with a slowly varying dissipation parameter.

Original languageEnglish (US)
Pages (from-to)1115-1130
Number of pages16
JournalSignal Processing
Volume84
Issue number7
DOIs
StatePublished - Jul 2004

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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