SYSTEM IDENTIFICATION OF ELECTRONIC NOSE DATA FOR MONITORING CYANO-BACTERIA IN POTABLE WATER: BLACK-BOX MODELLING

摘要

Linear black-box modelling techniques are applied to data collected from an electronic nose experiment. FIR, ARX, MAX and ARMAX inverse models of the nose system are used to discriminate between two different strains of cyanobacteria. Models for both pre-processed and raw data are proposed, and successful classification rates of 100% and 99.3% are obtained, respectively.