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Selective detection of hydrogen and carbon monoxide mixture in air against individual CO and H2 gases by means of a single MOX sensor is presented. Four different nanocrystalline SnO2 based sensing materials (pure SnO2, Au-, Co-, Fe- doped) were used in a dynamic working temperature mode. Data processing algorithms combined with artificial neural networks were applied to increase sensors selectivity of response. Accuracy of target gas mixture identification in dependence of applied sensing material is discussed. High precision of target gas mixture quantification is presented.