(2020) Ravashdeh, L. A. M.; Zakharov, I. P.; Zaporozhets, O. V.
A neural network compensator for the nonlinearity of a dynamic measuring instrument is proposed, which allows restoring the value of the measured input signal. The inverse model of a nonlinear dynamic measuring device is implemented based on a three-layer perceptron supplemented by delay lines of input signals. The properties of the proposed neural network compensator are studied through simulation computer modelling using various types of calibration input signals for the training of an artificial neural network.
(2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL), 2019) Запорожець, О. В.; Штефан, Н. О.
A method for correcting the transformation function of a semiconductor thermistor using a nonlinearity compensator based on a three-layer perceptron is proposed. Using of computer simulation, the operability of the proposed method has been investigated, a comparative analysis has been carried out with polynomial compensators of nonlinearity.