Evolutionary Selection of Features for Neural Sleep/Wake Discrimination

Abstract

In biomedical signal analysis, artificial neural networks are often used for pattern classification because of their capability for nonlinear class separation and the possibility to efficiently implement them on a microcontroller. Typically, the network topology is designed by hand, and a gradient-based search algorithm is used to find a set of suitable… (More)

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Cite this paper

@inproceedings{Drr2009EvolutionarySO, title={Evolutionary Selection of Features for Neural Sleep/Wake Discrimination}, author={Peter D{\"u}rr and Walter Karlen and J{\'e}r{\'e}mie Guignard and Dario Floreano}, year={2009} }