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Genetic algorithm wavelet design for signal classification

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5 Author(s)
Jones, E. ; Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA ; Runkle, P. ; Dasgupta, N. ; Couchman, L.
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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

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:23 ,  Issue: 8 )