Extended disjoint principal-components regression analysis of SAW vapor sensor-array responses
dc.contributor.author | Zellers, Edward T. | en_US |
dc.contributor.author | Pan, Tin-Su | en_US |
dc.contributor.author | Patrash, Samuel J. | en_US |
dc.contributor.author | Han, Mingwei | en_US |
dc.contributor.author | Batterman, Stuart A. | en_US |
dc.date.accessioned | 2006-04-10T15:48:14Z | |
dc.date.available | 2006-04-10T15:48:14Z | |
dc.date.issued | 1993-04-01 | en_US |
dc.identifier.citation | Zellers, Edward T., Pan, Tin-Su, Patrash, Samuel J., Han, Mingwei, Batterman, Stuart A. (1993/04/01)."Extended disjoint principal-components regression analysis of SAW vapor sensor-array responses." Sensors and Actuators B: Chemical 12(2): 123-133. <http://hdl.handle.net/2027.42/30857> | en_US |
dc.identifier.uri | http://www.sciencedirect.com/science/article/B6THH-449V4H9-2X/2/5b78bdd88ae5c73a0cc7d1a85bdf38c3 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/30857 | |
dc.description.abstract | The application of a disjoint principal-components regression method to the analysis of sensor-array response patterns is demonstrated using published data from ten polymer-coated surface-acoustic-wave (SAW) sensors exposed to each of nine vapors. Use of the method for the identification and quantitation of the components of vapor mixtures is shown by simulating the 36 possible binary mixtures and 84 possible ternary mixtures under the assumption of additive responses. Retaining information on vapor concentrations in the classification models allows vapors to be accurately identified, while facilitating prediction of the concentrations of individual vapors and the vapors comprising the mixtures. The effects on the rates of correct classification of placing constraints on the maximum and minimum vapor concentrations and superimposing error on the sensor responses are investigated. | en_US |
dc.format.extent | 1242849 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | en_US |
dc.title | Extended disjoint principal-components regression analysis of SAW vapor sensor-array responses | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Mechanical Engineering | en_US |
dc.subject.hlbsecondlevel | Industrial and Operations Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | University of Michigan, School of Public Health, Department of Environmental and Industrial Health, Ann Arbor, MI 48109-2029 USA | en_US |
dc.contributor.affiliationum | University of Michigan, School of Public Health, Department of Environmental and Industrial Health, Ann Arbor, MI 48109-2029 USA | en_US |
dc.contributor.affiliationum | University of Michigan, School of Public Health, Department of Environmental and Industrial Health, Ann Arbor, MI 48109-2029 USA | en_US |
dc.contributor.affiliationum | University of Michigan, School of Public Health, Department of Environmental and Industrial Health, Ann Arbor, MI 48109-2029 USA | en_US |
dc.contributor.affiliationum | University of Michigan, School of Public Health, Department of Environmental and Industrial Health, Ann Arbor, MI 48109-2029 USA | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/30857/1/0000520.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/0925-4005(93)80008-Y | en_US |
dc.identifier.source | Sensors and Actuators B: Chemical | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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