Gas Sensing Supported by Pattern Recognition

• Authors: C. Tyszkiewicz , A. Szpakowski , T. Pustelny
• Languages of publication: EN

Abstracts

EN

The system composed of the array of eight semiconductor, chemoresistive gas sensors was used for the classification of hydrogen, methane and carbon oxide gaseous samples. The classification task was performed by pattern recognition methods applied to the multivariate response of the array. The pattern recognition scheme used for classification uses a feature subset selection algorithm coupled with an objective function designed for clustering and a multilayer perceptron classifier.

Keywords

EN

02.50.Sk; 07.07.Df; 84.35.+i

Discipline

• 07.07.Df: Sensors (chemical, optical, electrical, movement, gas, etc.); remote sensing
• 84.35.+i: Neural networks(for optical neural networks, see 42.79.Ta; see also 07.05.Mh Neural networks, fuzzy logic, artificial intelligence in computers in experimental physics; 87.18.Sn in biological complexity)
• 02.50.Sk: Multivariate analysis

• Journal: Acta Physica Polonica A
• Year: 2009
• Volume: 116
• Issue: 3
• Pages: 419-421

Dates

published

2009-09

Contributors

author

C. Tyszkiewicz

• Department of Optoelectronics, Silesian University of Technology, Krzywoustego 2, 44-100 Gliwice, Poland

author

A. Szpakowski

• Department of Optoelectronics, Silesian University of Technology, Krzywoustego 2, 44-100 Gliwice, Poland

author

T. Pustelny

• Department of Optoelectronics, Silesian University of Technology, Krzywoustego 2, 44-100 Gliwice, Poland

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Identifiers

DOI

10.12693/APhysPolA.116.419