@article{Zamyatin_Smirnov_Makovkin_2022, title={Neural Network-Based Sensor Calibration for Micro and Nanoelectronics Applications}, volume={3}, url={https://en.jcyb.ru/nisii_tech/article/view/145}, DOI={10.51790/2712-9942-2022-3-3-8}, abstractNote={<p>we studied multilayer neural network-enabled calibration of optical gas sensor systems. Such systems use fiberoptic converters so their properties can be nonlinear and nonmonotonic. We used real-world data to show the proposed calibration method’s applicability. The neural network-based approach offers a higher quality of the calibration, and a multilayer neural network doe not need a training dataset to estimate the optical properties.</p&gt;}, number={3}, journal={Russian Journal of Cybernetics}, author={Zamyatin, N. V. and Smirnov, G. V. and Makovkin, V. I.}, year={2022}, month={Sep.}, pages={74-82} }