Abstract
This study explores the ability of wavelets and wavelet packets to extract information from non-stationary signals for the purpose of classification. The signals used were of two types: non-stationary signals from three marine mammals (dolphins, porpoises, and sperm whales), and quasi-stationary signals from an experimental undersea vehicle. This study also focuses on the impact of the compression ratio and the basis selection on the performance of a given classifier.
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References
R. R. Coifman, Y. Meyer, and M. V. Wickerhauser, Wavelet Analysis and Signal Processing, in Ruskai et al., eds., Wavelets and their Applications, Jones and Bartlett, Boston 1992, pp. 153–178.
W. Greene and Q. Huynh, Feature Extraction and Classification of Marine Biological Species, Proceedings of the International Conference on Theoretical and Computational Acoustics, D. Lee, J. Ffowcs-Williams, and A. D. Pierce (eds.), World Scientific Press, Singapore (to be published 1994).
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© 1995 Springer Science+Business Media Dordrecht
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Huynh, Q., Greene, W., Impagliazzo, J. (1995). Feature Extraction and Classification of Underwater Acoustic Signals. In: Diachok, O., Caiti, A., Gerstoft, P., Schmidt, H. (eds) Full Field Inversion Methods in Ocean and Seismo-Acoustics. Modern Approaches in Geophysics, vol 12. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8476-0_30
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DOI: https://doi.org/10.1007/978-94-015-8476-0_30
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4545-4
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