Multi-Task Spiking Neural Network for Simultaneous Vapor Recognition and Concentration Estimation

This dataset contains 2,016 sensor responses collected from an array of conductive carbon-black polymer composite sensors, exposed to four target analytes—acetonitrile, dichloromethane (DCM), methanol, and toluene—at nine distinct concentration levels ranging from 0.5% to 20% P/P₀. Each sensor was exposed to the analytes for 20 minutes, followed by 20 minutes of nitrogen flushing to restore the baseline. The data consists of 80 time points (one every 30 seconds) per response, with each time point representing the sensor's resistance to a specific analyte concentration. This dataset is designed to support pattern recognition tasks for gas sensor arrays in applications such as electronic noses. More details can be found in the article Multi-Task Spiking Neural Network for Simultaneous Vapor Recognition and Concentration Estimation.