Wavelets are widely used in numerous applied fields involving for example signal analysis, image compression or function approximation. 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 based on the lifting scheme. We apply the constructed wavelet for pattern detection in the 1D case. To do so, we propose a three stages detection procedure which is finally illustrated by spike detection in EEG.


Discrete Wavelet Transform Continuous Wavelet Transform Pattern Detection Lift Scheme Biorthogonal Wavelet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hector Mesa
    • 1
    • 2
  1. 1.Faculty of Mathematics and Computer SciencesUniversity of La HabanaLa HabanaCuba
  2. 2.Paris-Sud XI UniversityOrsay, ParisFrance

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