Classification of Non Stationary Signals Using Ben Wavelet and Artificial Neural Networks
| Main Authors: | Mohammed Benbrahim, Khalid Benjelloun, Aomar Ibenbrahim, Adil Daoudi |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2008
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1082153 |
Daftar Isi:
- 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.