Virtual arrays formed by operating temperature modulation of a commercial non selective chemoresistor have been utilized for gas identification. Here, we are reporting the details of a refined system which distinctly classifies methanol, ethanol, 1-butanol, acetone and hydrogen contaminations in a wide concentration range. A staircase voltage waveform of 5 plateaus is applied to the sensor’s microheater and gas recognition is achieved in 25 s. Sensor’s output is modeled by an “autoregressive moving average with exogenous variables” (ARMAX) model. The modeling parameters obtained for an unknown analyte are utilized as the components of its feature vectors which afford its classification in a feature space. Cross-validation in the 5 to 100 ppm concentration range for H2, and 200 to 2000 ppm for the other analytes examined, resulted in an overall classification success rate of 100%.