Date of Award
Master of Science
Department of Mathematics and Statistics
Gregory Warhola, PhD
The application of the multiresolution analysis developed by Mallat to signal classification by Pati and Krishnaprasad and Szu, et al, is further explored in this thesis. Several different wavelet based feature extraction and classification systems are developed and implemented. Methods which rely on the traditional dyadic wavelet decomposition and on the adaptive wavelet representation are presented. Each of the classification systems is implemented for a labeled data set of narrowband signals. Finally, classification results on the full data set and on low frequency Fourier coefficients are provided as baseline comparisons for our work.
DTIC Accession Number
Pohl, Anthony J., "Adaptive and Fixed Wavelet Features for Narrowband Signal Classification" (1995). Theses and Dissertations. 6122.