Change detection in time series using the maximal overlap discrete wavelet transform

Latin American Applied Research

Volumn 39, Issue 2, 2009, Pages 145-152

  Alarcon Aquinoy, V ^a   Barriaz, J A ^b  

^a UNIVERSIDAD DE LAS AMÉRICAS PUEBLA   (Mexico)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Change detection; Time series; Wavelet transforms; Wavelets

Indexed keywords

EID: 74549210399     PISSN: 03270793     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Alarcon-Aquino, V., Anomaly Detection and Predic- tion in Communication Networks Using Wavelet Transforms, PhD Thesis, Imperial College London, University of London (2003).
2. Alarcon-Aquino, V. and J.A. Barria, "Anomaly Detec- tion in Communication Networks Using Wavelets," IEE Proceedings - Communications, 148, 355-362 (2001).
3. Alarcon-Aquino, V. and J.A. Barria, "Multi-Sensor Fusion System Using Wavelet Based Detec- tion Algorithm Applied to Network Monitor- ing,"Proceedings of London Communication Sym- posium, 361-364 (2002).
4. Alarcon-Aquino, V. and J.A. Barria, "Multiresolu- tion FIR Neural Network Based Learning Al- gorithm Applied to Network Tra±c Prediction," IEEE Transactions on Systems, Man and Cyber- netics Part C: Applications and Review, 36, 208- 220 (2006).
5. Appel, U. and A.V. Brandt, "Adaptive Sequential Seg- mentation of Piecewise Stationary Time Series", Information Sciences, 29, 27-56 (1983).
6. Bakshi, B.R., "Multiscale Analysis and Modelling Us- ing Wavelets," Journal of Chemometrics, 13, 415- 434 (1999).
7. Bernardo, J.M. and A.F.M. Smith, Bayesian Theory, NY Wiley (1994)
8. Basseville, M. and I.V. Nikiforov, Detection of Abrupt Changes: Theory and Application. Information and System Science Series. Englewood Cliffs, NJ: Prentice-Hall (1993).
9. Daubechies, I. Ten Lectures on Wavelets, New York: SIAM (1992).
10. Gustafsson, F., "The Marginalised Likelihood Ratio Test for Detecting Abrupt Changes," IEEE Trans- actions on Automatic Control, 41, 66-78 (1996).
11. Khalil, M. and J. Duchene, "Detection and Classi-ca- tion of Multiple Events in Piecewise Stationary Sig- nal: Comparison between autoregressive and mul- tiscale approaches," Signal Processing, 75, 239-251 (1999).
12. Kobayashi, M.,"Wavelet Analysis and Their Applica- tions in Industry," Nonlinear Analysis, 47, 1749- 1760 (2001).
13. Mallat, S. A Wavelet Tour of Signal Processing, Aca- demic Press (1999).
14. Percival, D.B. and A.T. Walden, Wavelet Methods for Time Series Analysis. Cambridge University Press (2000)
15. Salam, M-S., D. Mohaman and S-H Salleh, "Seg- mentation of Malay Syllables in Connected Digit Speech Using Statistical Approach," International Journal of Computer Science and Security, 2, 23- 33 (2008).
16. Tseng,V.S., C.H. Chen, C-H Chen and T-P Hong., "Segmentation of Time Series by the Clustering and Genetic Algorithms," in Proceedings of the Sixth International Conference on Data Mining- Workshops ICDMW06 (2006).