Investigation of Spectral-Based Techniques for Classification of Wideband Transient Signals in Additive White Gaussian Noise
NAVAL POSTGRADUATE SCHOOL MONTEREY CA
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Spectral-based classification schemes designed to separate various wide band transient signals in added noise have been identified and their performances compared along with those obtained using a back-propagation neural network implementation. The spectral-based measures used include the normalized cross-correlation coefficient the modified normalized cross-correlation coefficient, and the divergence and the Bhattacharyya distance. Noise was added to the signals to create signal to noise ratios of 0 dB to -20 dB. Results show that as noise levels increase, the modified normalized cross-correlation coefficient spectral measure remains the most robust scheme.
- Atomic and Molecular Physics and Spectroscopy