Genetic algorithm wavelet design for signal classification

Authors
Jones, E Runkle, P Dasgupta, N Couchman, L Carin, L
Citation
E. Jones et al., Genetic algorithm wavelet design for signal classification, IEEE PATT A, 23(8), 2001, pp. 890-895
Citations number
22
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
ISSN journal
01628828 → ACNP
Volume
23
Issue
8
Year of publication
2001
Pages
890 - 895
Database
ISI
SICI code
0162-8828(200108)23:8<890:GAWDFS>2.0.ZU;2-3
Abstract
Biorthogonal wavelets are applied to parse multiaspect transient scattering data in the context of signal classification. A language-based genetic alg orithm is used to design wavelet filters that enhance classification perfor mance. The biorthogonal wavelets are implemented via the lifting procedure and the optimization is carried out using a classification-based cost funct ion. Example results are presented for target classification using measured scattering data.