Abstract
been proposed and used in classification of prehensile surface EMG patterns. The new method has essentially extended the Englehart’s discrete wavelet transform and wavelet packet transform by introducing more efficient feature reduction method that also offered better generalization. The approaches were empirically evaluated on the same set of signals recorded from two real subjects, and by using the same classifier, which was the Vapnik’s support vector machine.
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Carreño, I.R., Vuskovic, M. (2007). Wavelet Transform Moments for Feature Extraction from Temporal Signals. In: Filipe, J., Ferrier, JL., Cetto, J.A., Carvalho, M. (eds) Informatics in Control, Automation and Robotics II. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5626-0_28
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