Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing.The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications.  Therefore, in order to obtain more useful information and improve the E-nose's classification accuracy, in this paper, a Weighted Kernels Fisher Discriminant Analysis (WKFDA) combined with Quantum-behaved Particle Swarm Optimization (QPSO), i.e., QWKFDA, was presented to reprocess the original feature matrix. 
QPSO
Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing.The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications. 
Multiple KFDA Signal Processing