HYBRID CLASSIFICATION SCHEMES FOR HEART MURMUR DETECTION TO ASSIST PHONOCARDIOGRAM BASED SIGNAL ACQUISITION
Journal Title: JOURNAL OF ADVANCES IN CHEMISTRY - Year 2017, Vol 13, Issue 9
Abstract
The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.
Authors and Affiliations
A. D. Jeyarani, Reena Daphne, Solomon Roach
Keywords
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- EP ID EP653125
- DOI 10.24297/jac.v13i9.5803
- Views 170
- Downloads 0
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