Two Algorithms for Processing Electronic Nose Data

It is necessary to find the minimum point on the electronic-nose error surface for each pair of vapors. In the present version of the algorithm, this is done by sampling values on a grid and selecting the sample that has the minimum value. In a subsequent enhanced version of the algorithm, a more sophisticated technique (e.g., gradient descent) might be used to find the minimum. The pair of vapors for which the electronic-nose error surface has the lowest minimum value is deemed to be identified as the vapor pair sensed by the electronic nose. Provided that this identification is correct, the concentrations of the two vapors are the coordinates of the location of the minimum on the error surface for that pair.

The validity of the single-vapor algorithm depends on the validity of the assumption that, of all the vapors of interest, only one is present at the time of measurement. This algorithm utilizes the following mathematical model of the response of a given sensor to a single vapor:

where z is the sensor response, x is the concentration of the vapor, and parameters A and B are obtained by leastsquares best fit of sensor responses at known values of x. This model is appropriate because it gives both the expected zero response at zero concentration and saturation response at high concentration.