WAVELET TRANSFORM MOMENTS FOR FEATURE EXTRACTION FROM TEMPORAL SIGNALS

Ignacio Rodriguez Carreño, Marko Vuskovic

2005

Abstract

A new feature extraction method based on five moments applied to three wavelet transform sequences has 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.

Paper Citation

in Harvard Style

Rodriguez Carreño I. and Vuskovic M. (2005). WAVELET TRANSFORM MOMENTS FOR FEATURE EXTRACTION FROM TEMPORAL SIGNALS . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 972-8865-31-7, pages 71-78. DOI: 10.5220/0001190100710078

in Bibtex Style

@conference{icinco05,
author={Ignacio Rodriguez Carreño and Marko Vuskovic},
title={WAVELET TRANSFORM MOMENTS FOR FEATURE EXTRACTION FROM TEMPORAL SIGNALS},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2005},
pages={71-78},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001190100710078},
isbn={972-8865-31-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - WAVELET TRANSFORM MOMENTS FOR FEATURE EXTRACTION FROM TEMPORAL SIGNALS
SN - 972-8865-31-7
AU - Rodriguez Carreño I.
AU - Vuskovic M.
PY - 2005
SP - 71
EP - 78
DO - 10.5220/0001190100710078