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<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>
Genetic algorithms, wavelets, classification.

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.
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