Detection Algorithms for the Nano Nose

The nano nose is an instrument with an array of nano sized optical sensors that produces digital patterns when exposed to radiation passing through a gaseous mixture. This paper outlines an algorithm using a combination of neural networks and partial least squares (PLS) regression, Kalman filter capable of processing these digital patterns and generate an output. This output would not only show the detection of the individual constituents in the gaseous mixture but also the prediction of their concentrations. The developed algorithm in the experiments conducted, has performed detection and prediction of quite low concentrations of constituent gases successfully with a prediction error of less than 10% in the presence of noise.