Geodesic
Locally weighted neural networks for an analysis of the biosensor response
Kybernetika, Tome 43 (2007) no. 1, pp. 21-30.

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This paper presents a semi-global mathematical model for an analysis of a signal of amperometric biosensors. Artificial neural networks were applied to an analysis of the biosensor response to multi-component mixtures. A large amount of the learning and test data was synthesized using computer simulation of the biosensor response. The biosensor signal was analyzed with respect to the concentration of each component of the mixture. The paradigm of locally weighted linear regression was used for retraining the neural networks. The application of locally weighted regression significantly improved the quality of the prediction of the concentrations.
Classification : 62J12, 62M45, 62P10, 68T05, 92C45, 92C55
Keywords: locally weighted regression; artificial neural network; modelling; biosensor 
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     author = {Baronas, Romas and Ivanauskas, Feliksas and Maslovskis, Romualdas and Radavi\v{c}ius, Marijus and Vaitkus, Pranas},
     title = {Locally weighted neural networks for an analysis of the biosensor response},
     journal = {Kybernetika},
     pages = {21--30},
     publisher = {mathdoc},
     volume = {43},
     number = {1},
     year = {2007},
     mrnumber = {2343328},
     zbl = {1136.62374},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_2007__43_1_a1/}
}
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Baronas, Romas; Ivanauskas, Feliksas; Maslovskis, Romualdas; Radavičius, Marijus; Vaitkus, Pranas. Locally weighted neural networks for an analysis of the biosensor response. Kybernetika, Tome 43 (2007) no. 1, pp. 21-30. http://geodesic.mathdoc.fr/item/KYB_2007__43_1_a1/