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Full-Text Articles in Engineering
Adaptive And Fixed Wavelet Features For Narrowband Signal Classification, Anthony J. Pohl
Adaptive And Fixed Wavelet Features For Narrowband Signal Classification, Anthony J. Pohl
Theses and Dissertations
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.
Space Object Identification Using Spatio-Temporal Pattern Recognition, Gary W. Brandstrom
Space Object Identification Using Spatio-Temporal Pattern Recognition, Gary W. Brandstrom
Theses and Dissertations
This thesis is part of a research effort to automate the task of characterizing space objects or satellites based on a sequence of images. The goal is to detect space object anomalies. Two algorithms are considered - the feature space trajectory neural network (FST NN) and hidden Markov model (HMM) classifier. The FST NN was first presented by Leonard Neiberg and David P. Casasent in 1994 as a target identification tool. Kenneth H. Fielding and Dennis W. Ruck recently applied the hidden Markov model classifier to a 3D moving light display identification problem and a target recognition problem, using time …