Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers

P. Kaufmann, K. Glette, T. Gruber, M. Platzner, J. Torresen, B. Sick, IEEE Transactions on Evolutionary Computation 17 (2013) 46–63.

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Journal Article | English
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IEEE Transactions on Evolutionary Computation
Volume
17
Issue
1
Page
46-63
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Kaufmann P, Glette K, Gruber T, Platzner M, Torresen J, Sick B. Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers. IEEE Transactions on Evolutionary Computation. 2013;17(1):46-63. doi:10.1109/TEVC.2012.2185845
Kaufmann, P., Glette, K., Gruber, T., Platzner, M., Torresen, J., & Sick, B. (2013). Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers. IEEE Transactions on Evolutionary Computation, 17(1), 46–63. https://doi.org/10.1109/TEVC.2012.2185845
@article{Kaufmann_Glette_Gruber_Platzner_Torresen_Sick_2013, title={Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers}, volume={17}, DOI={10.1109/TEVC.2012.2185845}, number={1}, journal={IEEE Transactions on Evolutionary Computation}, author={Kaufmann, Paul and Glette, Kyrre and Gruber, Tiemo and Platzner, Marco and Torresen, Jim and Sick, Bernhard}, year={2013}, pages={46–63} }
Kaufmann, Paul, Kyrre Glette, Tiemo Gruber, Marco Platzner, Jim Torresen, and Bernhard Sick. “Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers.” IEEE Transactions on Evolutionary Computation 17, no. 1 (2013): 46–63. https://doi.org/10.1109/TEVC.2012.2185845.
P. Kaufmann, K. Glette, T. Gruber, M. Platzner, J. Torresen, and B. Sick, “Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers,” IEEE Transactions on Evolutionary Computation, vol. 17, no. 1, pp. 46–63, 2013.
Kaufmann, Paul, et al. “Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers.” IEEE Transactions on Evolutionary Computation, vol. 17, no. 1, 2013, pp. 46–63, doi:10.1109/TEVC.2012.2185845.

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