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.
|Original language||English (US)|
|Number of pages||6|
|Journal||IEEE Transactions on Pattern Analysis and Machine Intelligence|
|State||Published - Aug 1 2001|