Symbolic dynamic analysis of complex systems for anomaly detection

Authors:
Asok Ray
Affiliations:
Mechanical Engineering Department, 137, Reber Building, The Pennsylvania State University, University Park, PA
Venue:
Signal Processing
Year:
2004

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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.