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On the Capability of Artificial Neural Networks to Compensate Nonlinearities in Wavelength Sensing
Laboratoire d’Electronique Avancée, Département d’Electronique, Université de Batna, 05 avenue Chahid Boukhlouf 05000 Batna, Algeria
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
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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Cite This Article
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.
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.
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.