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| Paper: | SPTM-P13.10 |
| Session: | Detection and Classification |
| Time: | Friday, May 21, 15:30 - 17:30 |
| Presentation: |
Poster |
| Topic: |
Signal Processing Theory and Methods: Detection, Estimation, and Class. Thry & Apps. |
| Title: |
OPTIMAL WAVELET FOR ABRUPT CHANGE DETECTION IN MULTIPLICATIVE NOISE |
| Authors: |
Marie Chabert; ENSEEIHT/IRIT/TéSA | | |
| | Daniel Ruiz; ENSEEIHT/IRIT | | |
| | Jean-Yves Tourneret; ENSEEIHT/IRIT/TéSA | | |
| Abstract: |
This paper addresses abrupt change detection in multiplicative noise using the continous wavelet transform. An optimal wavelet, maximizing a well-chosen time-scale contrast criterion is derived. The analytical optimization gives the optimal wavelet closed expression. The influence of the mother wavelet on signature-based detector performance is then demonstrated. Detection performance is characterized using Receiver Operating Characteristic curves computed from Monte-Carlo simulations. The optimal wavelet obviously improves performance with respect to other wavelets classicaly used for singularity detection. |
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