Title :
Genetic algorithm wavelet design for signal classification
Author :
Jones, Eric ; Runkle, Paul ; Dasgupta, Nilanjan ; Couchman, Luise ; Carin, Lawrence
Author_Institution :
Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
fDate :
8/1/2001 12:00:00 AM
Abstract :
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
Keywords :
filtering theory; genetic algorithms; signal classification; wavelet transforms; GA; biorthogonal wavelets; classification-based cost function; genetic algorithm wavelet design; language-based genetic algorithm; lifting procedure; measured scattering data; multiaspect transient scattering data parsing; optimization; signal classification; target classification; wavelet filter design; Algorithm design and analysis; Cost function; Discrete wavelet transforms; Filter bank; Finite impulse response filter; Genetic algorithms; Pattern classification; Scattering; Signal design; Wavelet analysis;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
