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ABSTRACT
<p><b>Abstract</b>—Biorthogonal wavelets are applied to parse multiaspect transient scattering data in the context of signal classification. A language-based genetic algorithm is used to design wavelet filters that enhance classification performance. The biorthogonal wavelets are implemented via the lifting procedure and the optimization is carried out using a classification-based cost function. Example results are presented for target classification using measured scattering data.</p>
INDEX TERMS
Genetic algorithms, wavelets, classification.
CITATION

E. Jones, L. Carin, L. Couchman, P. Runkle and N. Dasgupta, "Genetic Algorithm Wavelet Design for Signal Classification," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 23, no. , pp. 890-895, 2001.
doi:10.1109/34.946991
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