Classification Of Non Stationary Signals Using Ben Wavelet And Artificial Neural Networks
Mohammed Benbrahim, Khalid Benjelloun, Aomar Ibenbrahim, Adil Daoudi · Zenodo (CERN European Organization for Nuclear Research) · 2008
The automatic classification of non stationary signals is an important practical goal in several domains. An essential classification task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "Ben wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.