Garcia-Breijo, E.; J.K. Atkinson; Gil Sánchez, L.; Masot Peris, R.; Ibáñez Civera, FJ.; Garrigues Baixauli, J.; M. Glanc... (2011). A comparison study of pattern recognition algorithms implemented on a microcontroller for use in an electronic tongue for monitoring drinking waters. Sensors and Actuators A: Physical. 172:570-582. https://doi.org/10.1016/j.sna.2011.09.039
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/72663
Title:
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A comparison study of pattern recognition algorithms implemented on a microcontroller for use in an electronic tongue for monitoring drinking waters
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Author:
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Garcia-Breijo, Eduardo
J.K. Atkinson
Gil Sánchez, Luís
Masot Peris, Rafael
Ibáñez Civera, Francisco Javier
Garrigues Baixauli, José
M. Glanc
Laguarda-Miro, Nicolas
Olguín Pinatti, Cristian Ariel
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UPV Unit:
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Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica
Universitat Politècnica de València. Departamento de Ingeniería Química y Nuclear - Departament d'Enginyeria Química i Nuclear
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Issued date:
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Abstract:
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A portable electronic tongue has been developed using an array of eighteen thick-film electrodes of different
materials forming a multi-electrode array. A microcontroller is used to implement the pattern
recognition. The ...[+]
A portable electronic tongue has been developed using an array of eighteen thick-film electrodes of different
materials forming a multi-electrode array. A microcontroller is used to implement the pattern
recognition. The classification of drinking waters is carried out by a Microchip PIC18F4550 microcontroller
and is based on neural networks algorithms. These algorithm are initially trained with the
multi-electrode array on a Personal Computer (PC) using several samples of waters (still, sparkling and
tap) to obtain the optimum architecture of the networks. Once it is trained, the computed data are programmed
into the microcontroller, which then gives the water classification directly for new unknown
water samples. A comparative study between a Fuzzy ARTMAP, a Multi-Layer Feed-Forward network
(MLFF) and a Linear DiscriminantAnalysis (LDA) has been done in order to obtain the bestimplementation
on a microcontroller.
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Subjects:
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Thick-film Microcontroller
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Neural network
,
Electronic tongue
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Pattern recognition
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Copyrigths:
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Reserva de todos los derechos
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Source:
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Sensors and Actuators A: Physical. (issn:
0924-4247
)
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DOI:
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10.1016/j.sna.2011.09.039
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Publisher:
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Elsevier
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Publisher version:
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http://dx.doi.org/10.1016/j.sna.2011.09.039
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Project ID:
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info:eu-repo/grantAgreement/GVA//BEST%2F2010%2F138/
info:eu-repo/grantAgreement/UPV//PAID-00-10/
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Thanks:
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Dr. E. Garcia gratefully acknowledges financial support (grant BEST/2010/138) from the Generalitat Valenciana and (grant PAID-00-10) from the Universidad Politecnica de Valencia during his stay at the University of ...[+]
Dr. E. Garcia gratefully acknowledges financial support (grant BEST/2010/138) from the Generalitat Valenciana and (grant PAID-00-10) from the Universidad Politecnica de Valencia during his stay at the University of Southampton. We also thank MICINN (MAT2009-14564-C04-02).
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Type:
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Artículo
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