Agamyrat Agambayev

Discrete Cosine Transform Based Causal Convolutional Neural Network for Drift Compensation in Chemical Sensors

Sensor drift is a major problem in chemical sensors that requires addressing for reliable and accurate detection of chemical analytes. In this paper, we develop a causal convolutional neural network (CNN) with a Discrete Cosine Transform (DCT) layer to estimate the drift signal. In the DCT module, w…