TY - JOUR
T1 - Symbolic dynamic analysis of complex systems for anomaly detection
AU - Ray, Asok
N1 - Funding Information:
This work has been supported in part by Army Research Office (ARO) under Grant No. DAAD19-01-1-0646; and NASA Glenn Research Center under Grant No. NNC04GA49G.
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2004/7
Y1 - 2004/7
N2 - 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.
AB - 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.
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U2 - 10.1016/j.sigpro.2004.03.011
DO - 10.1016/j.sigpro.2004.03.011
M3 - Article
AN - SCOPUS:2642522033
SN - 0165-1684
VL - 84
SP - 1115
EP - 1130
JO - Signal Processing
JF - Signal Processing
IS - 7
ER -