Wavelets are widely used in numerous applied fields involv-ing for example signal analysis, image compression or function approxi-mation. The idea of adapting wavelet to specific problems, it means to create and use problem and data dependent wavelets, has been developed for various purposes. In this paper, we are interested in to define, starting from a given pattern, an efficient design of FIR adapted wavelets baaed on the lifting scheme. We apply the constructed wavelet for pattern de-tection in the 1D case, To do so, we propose a three stages detection procedure which is finally illustrated by spike detection in EEC. © Springer-Vorlag Berlin Heidelberg 2005.
CITATION STYLE
Mesa, H. (2005). Adapted wavelets for pattern detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3773 LNCS, pp. 933–944). https://doi.org/10.1007/11578079_96
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