For verification of the proposed method, We use two datasets, the first dataset is the real sensor drift benchmark dataset of three years collected by an E-nose from Vergara et al. in UCSD, the detailed can be found in the following paper:
Chemical gas sensor drift compensation using classifier ensembles

the second datset is from our lab.

If you find our job useful, please cite our paper "L. Zhang, Y. Liu, Z. He, J. Liu, P. Deng, and X. Zhou, Anti-Drift in E-nose: A Subspace Projection Approach with Drift Reduction," Sensors and Actuators B: Chemical, 2017.

