Hdl Handle:
http://hdl.handle.net/10149/97951
Title:
Data analysis for electronic nose systems
Authors:
Scott, S. M. (Simon); James, D. (David); Ali, Z. (Zulfiqur)
Affiliation:
University of Teesside. School of Science and Technology. Applied Science Department.
Citation:
Scott, S. M., James, D. and Ali, Z. (2006) 'Data analysis for electronic nose systems', Microchimica Acta, 156 (3/4), pp.183-207.
Publisher:
Springer Wien
Journal:
Microchimica Acta
Issue Date:
Dec-2006
URI:
http://hdl.handle.net/10149/97951
DOI:
10.1007/s00604-006-0623-9
Abstract:
Electronic noses (e-noses) employ an array of chemical gas sensors and have been widely used for the analysis of volatile organic compounds. Pattern recognition provides a higher degree of selectivity and reversibility to the systems leading to an extensive range of applications. These range from the food and medical industry to environmental monitoring and process control. Many types of data analysis techniques have been used on the data produced. This review covers aspects of analysis from data normalisation methods to pattern recognition and classification techniques. An overview of data visualisation such as non-linear mapping and multivariate statistical techniques is given. Focus is then on the use of artificial intelligence techniques such as neural networks and fuzzy logic for classification and genetic algorithms for feature (sensor) selection. Application areas are covered with examples of the types of systems and analysis methods currently in use. Future trends in the analysis of sensor array data are discussed.
Type:
Article
Language:
en
Keywords:
electronic noses; pattern recognition; sensor arrays; sensor selections
ISSN:
0026-3672; 1436-5073
Rights:
Author can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo/ [Accessed 05/05/2010]
Citation Count:
42 [Scopus, 05/05/2010]

Full metadata record

DC FieldValue Language
dc.contributor.authorScott, S. M. (Simon)en
dc.contributor.authorJames, D. (David)en
dc.contributor.authorAli, Z. (Zulfiqur)en
dc.date.accessioned2010-05-05T13:17:42Z-
dc.date.available2010-05-05T13:17:42Z-
dc.date.issued2006-12-
dc.identifier.citationMicrochimica Acta; 156(3/4):183-207en
dc.identifier.issn0026-3672-
dc.identifier.issn1436-5073-
dc.identifier.doi10.1007/s00604-006-0623-9-
dc.identifier.urihttp://hdl.handle.net/10149/97951-
dc.description.abstractElectronic noses (e-noses) employ an array of chemical gas sensors and have been widely used for the analysis of volatile organic compounds. Pattern recognition provides a higher degree of selectivity and reversibility to the systems leading to an extensive range of applications. These range from the food and medical industry to environmental monitoring and process control. Many types of data analysis techniques have been used on the data produced. This review covers aspects of analysis from data normalisation methods to pattern recognition and classification techniques. An overview of data visualisation such as non-linear mapping and multivariate statistical techniques is given. Focus is then on the use of artificial intelligence techniques such as neural networks and fuzzy logic for classification and genetic algorithms for feature (sensor) selection. Application areas are covered with examples of the types of systems and analysis methods currently in use. Future trends in the analysis of sensor array data are discussed.en
dc.language.isoenen
dc.publisherSpringer Wienen
dc.rightsAuthor can archive post-print (ie final draft post-refereeing). For full details see http://www.sherpa.ac.uk/romeo/ [Accessed 05/05/2010]en
dc.subjectelectronic nosesen
dc.subjectpattern recognitionen
dc.subjectsensor arraysen
dc.subjectsensor selectionsen
dc.titleData analysis for electronic nose systemsen
dc.typeArticleen
dc.contributor.departmentUniversity of Teesside. School of Science and Technology. Applied Science Department.en
dc.identifier.journalMicrochimica Actaen
ref.citationcount42 [Scopus, 05/05/2010]en
or.citation.harvardScott, S. M., James, D. and Ali, Z. (2006) 'Data analysis for electronic nose systems', Microchimica Acta, 156 (3/4), pp.183-207.-
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