| 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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