Pattern analysis techniques for identification of individual gases using response of a poorly selective solid state sensor array

Abstract

Identification of odors/gases using an array of chemical sensors is a challenging task. The cross-sensitivity of individual gases results in poor selectivity. This makes identification of individual gases a computationally demanding task. Thus, there arises a strong need for efficient pattern analysis/computational models which could take into picture the high correlation in data due to the cross sensitivities of sensors while performing classification task.