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dc.contributor.authorSánchez-Montañés Isla, Manuel Antonio 
dc.contributor.authorGardner, Julian W.
dc.contributor.authorPearce, Timothy C.
dc.contributor.otherUAM. Departamento de Ingeniería Informáticaes_ES
dc.date.accessioned2015-05-07T17:57:33Z
dc.date.available2015-05-07T17:57:33Z
dc.date.issued2008-04-08
dc.identifier.citationProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 464 (2008): 1057–1077en_US
dc.identifier.issn1471-2946 (online)en_US
dc.identifier.issn1364-5021 (print)en_US
dc.identifier.urihttp://hdl.handle.net/10486/666063
dc.descriptionFirst publication of the article by the Royal Society of Chemistry.en_US
dc.description.abstractDeploying chemosensor arrays in close proximity to stationary phases imposes stimulus-dependent spatio-temporal dynamics on their response and leads to improvements in complex odour discrimination. These spatio-temporal dynamics need to be taken into account explicitly when considering the detection performance of this new odour sensing technology, termed an artificial olfactory mucosa. For this purpose, we develop here a new measure of spatio-temporal information that combined with an analytical model of the artificial mucosa, chemosensor and noise dynamics completely characterizes the discrimination capability of the system. This spatio-temporal information measure allows us to quantify the contribution of both space and time to discrimination performance and may be used as part of optimization studies or calculated directly from an artificial mucosa output. Our formal analysis shows that exploiting both space and time in the mucosa response always outperforms the use of space alone and is further demonstrated by comparing the spatial versus spatio-temporal information content of mucosa experimental data. Together, the combination of the spatio-temporal information measure and the analytical model can be applied to extract the general principles of the artificial mucosa design as well as to optimize the physical and operating parameters that determine discrimination performance.en_US
dc.description.sponsorshipWe also acknowledge the support of the Royal Society via a Joint European Research Project (to T.C.P. and M.A.S.-M.) and Engineering and Physical Sciences Research Council (to T.C.P. and J.W.G.). M.A.S.-M. was also supported by MEC (grant BFU2006-07902/BFI) and CAM (PRICIT 5-SEM-0255-2006).en_US
dc.format.extent22 pág.es_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherThe Royal Society of Chemistryen_US
dc.relation.ispartofProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciencesen_US
dc.rights© Royal Society of Chemistry 2008en_US
dc.subject.otherArtificial olfactory mucosaen_US
dc.subject.otherInformation theoryen_US
dc.subject.otherMachine olfactionen_US
dc.titleSpatio-temporal information in an artificial olfactory mucosaen_US
dc.typearticleen_US
dc.subject.ecienciaInformáticaes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1098/rspa.2007.0140
dc.identifier.doi10.1098/rspa.2007.0140
dc.identifier.publicationfirstpage1057
dc.identifier.publicationlastpage1077
dc.identifier.publicationvolume464
dc.relation.projectIDComunidad de Madrid. S2006/SEM-0255/OLFACTOSENSEes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.contributor.groupNeurocomputación Biológica (ING EPS-005)es_ES
dc.rights.ccReconocimientoes_ES
dc.rights.accessRightsopenAccessen
dc.authorUAMSánchez-Montañés Isla, Manuel Antonio (258772)
dc.facultadUAMEscuela Politécnica Superior


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