Wavelet-based space partitioning for symbolic time series analysis

被引：0

作者：

Rajagopalan, Venkatesh ^{[1
]}

Ray, Asok ^{[1
]}

机构：

[1] Penn State Univ, University Pk, PA 16802 USA

来源：

2005 44th IEEE Conference on Decision and Control & European Control Conference, Vols 1-8 | 2005年

关键词：

symbolic time series analysis; wavelets; fault detection; complex systems;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：5245 / 5250

页数：6

共 9 条

[1] Abry P., 1997, ONDELETTES TURBULENC
[2] [Anonymous], COMPUTATIONAL SIGNAL
[3] Symbolic time series analysis for anomaly detection: A comparative evaluation
Chin, SC
Ray, A
Rajagopalan, V
[J]. SIGNAL PROCESSING, 2005, 85 (09) : 1859 - 1868
[4] A review of symbolic analysis of experimental data
Daw, CS
Finney, CEA
Tracy, ER
[J]. REVIEW OF SCIENTIFIC INSTRUMENTS, 2003, 74 (02) : 915 - 930
[5] Kantz H, 2004, NONLINEAR TIME SERIE, DOI DOI 10.1017/CBO9780511755798
[6] Kennel MB, 2003, PHYS REV LETT, V91, DOI [10.1103/PhysRevLett.91.084102, 10.1063/1.1612266]
[7] MALLAT S, 1998, WAVELET TOUR SIGNA E, V2
[8] RAJAGOPALAN V, 2004, IASTED CSS
[9] Ray A., 2004, SYMBOLIC DYNAMIC ANA, V84

← 1 →