TY - GEN
T1 - Wavelet-based space partitioning for symbolic time series analysis
AU - Rajagopalan, Venkatesh
AU - Ray, Asok
PY - 2005
Y1 - 2005
N2 - Recent literature has reported symbolic time series analysis of complex systems for real-time anomaly detection. A crucial aspect in this analysis is symbol sequence generation from the observed time series data. This paper presents a wavelet-based partitioning, instead of the currently practiced method of phase-space partitioning, for symbol generation. The partitioning algorithm makes use of the maximum entropy method. The wavelet-space and phase-space partitioning methods are compared with regard to anomaly detection using experimental data.
AB - Recent literature has reported symbolic time series analysis of complex systems for real-time anomaly detection. A crucial aspect in this analysis is symbol sequence generation from the observed time series data. This paper presents a wavelet-based partitioning, instead of the currently practiced method of phase-space partitioning, for symbol generation. The partitioning algorithm makes use of the maximum entropy method. The wavelet-space and phase-space partitioning methods are compared with regard to anomaly detection using experimental data.
UR - http://www.scopus.com/inward/record.url?scp=33847195722&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33847195722&partnerID=8YFLogxK
U2 - 10.1109/CDC.2005.1582995
DO - 10.1109/CDC.2005.1582995
M3 - Conference contribution
AN - SCOPUS:33847195722
SN - 0780395689
SN - 9780780395688
T3 - Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
SP - 5245
EP - 5250
BT - Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
T2 - 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05
Y2 - 12 December 2005 through 15 December 2005
ER -