Neural network approximation of the thermometric characteristic of a diode sensor

Abstract

For the mathematical description of the thermometric characteristics of silicon thermodiode sensors, a neural network algorithm was used for the first time to approximate experimental data. The achieved high accuracy of approximation (≈1.5 mK) in the temperature range of 4.2–357 K made it possible to overcome the problems associated with processing experimental data using the polynomial approximation method.