Drift counteraction in odour recognition applications: lifelong calibration method

Sensor drift is addressed as one of the most serious impairments afflicting chemical and biochemical sensors. One possible solution to this problem is to view sensor arrays as time-varying dynamic systems, whose variations have to be tracked by adaptive estimation algorithms. A theory of hidden variable dynamics for the rejection of common mode drifting of sensors has previously been developed and is here coupled with a recursive least squares algorithm. In Section 7 a smart solution is provided for a difficult vapour recognition problem vexed by drift that have failed with traditional pattern recognition techniques. Among the many advantages we distinguish that model adaptation to changes in the sensor array makes lifelong calibration possible without interrupting the operation of the array.