Abstract
The paper presents examples of artificial neural networks approach for analysis of gas sensors responses. The research focused on quantitative analysis of gas mixtures appearing in dry and humid air. Despite difficulties in development of selective gas sensors, application of neural networks as self tuning signal processors provide construction of sensor systems capable of reliable measurements as well as analysis of gas mixtures with reasonable accuracy. Possibility of implementation of neural processing in low-cost devices enables eventual fabrication of microsystems integrating gas sensor matrices with intelligent data processing devices.
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Licznerski, B.W., Szecówka, P.M., Szczurek, A., Nitsch, K. (2000). Non Selective Gas Sensors and Artificial Neural Networks – Determination of Gas Mixtures. In: Kopacek, P., Moreno-Díaz, R., Pichler, F. (eds) Computer Aided Systems Theory - EUROCAST’99. EUROCAST 1999. Lecture Notes in Computer Science, vol 1798. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10720123_50
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DOI: https://doi.org/10.1007/10720123_50
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