Sensors 2009, 9(4), 2884-2894; doi:10.3390/s90402884
Article

On the Capability of Artificial Neural Networks to Compensate Nonlinearities in Wavelength Sensing

1 Laboratoire d’Electronique Avancée, Département d’Electronique, Université de Batna, 05 avenue Chahid Boukhlouf 05000 Batna, Algeria 2 Institut für Technische Informatik und Mikroelektronik, Technische Universität Berlin, Germany
* Author to whom correspondence should be addressed.
Received: 6 April 2009; in revised form: 6 April 2009 / Accepted: 21 April 2009 / Published: 21 April 2009
(This article belongs to the Special Issue Neural Networks and Sensors)
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Abstract: An intelligent sensor for light wavelength readout, suitable for visible range optical applications, has been developed. Using buried triple photo-junction as basic pixel sensing element in combination with artificial neural network (ANN), the wavelength readout with a full-scale error of less than 1.5% over the range of 400 to 780 nm can be achieved. Through this work, the applicability of the ANN approach in optical sensing is investigated and compared with conventional methods, and a good compromise between accuracy and the possibility for on-chip implementation was thus found. Indeed, this technique can serve different purposes and may replace conventional methods.
Keywords: Buried photo PN junctions; Artificial Neural Network; wavelength measurement

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MDPI and ACS Style

Hafiane, M.L.; Dibi, Z.; Manck, O. On the Capability of Artificial Neural Networks to Compensate Nonlinearities in Wavelength Sensing. Sensors 2009, 9, 2884-2894.

AMA Style

Hafiane ML, Dibi Z, Manck O. On the Capability of Artificial Neural Networks to Compensate Nonlinearities in Wavelength Sensing. Sensors. 2009; 9(4):2884-2894.

Chicago/Turabian Style

Hafiane, Mohamed Lamine; Dibi, Zohir; Manck, Otto. 2009. "On the Capability of Artificial Neural Networks to Compensate Nonlinearities in Wavelength Sensing." Sensors 9, no. 4: 2884-2894.

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