Performance of Machine Olfaction: Effect of Uniqueness of the Initial Data and Information Coding on the Discrimination Ability of Multisensor Arrays (Articolo in rivista)

Type

• Articolo in rivista (Classe)
• Prodotto della ricerca (Classe)

Label

• Performance of Machine Olfaction: Effect of Uniqueness of the Initial Data and Information Coding on the Discrimination Ability of Multisensor Arrays (Articolo in rivista) (literal)

Anno

• 2011-01-01T00:00:00+01:00 (literal)

Alternative label

• Burlachenko JV, Snopok BA, Capone S, Siciliano P (2011)
  Performance of Machine Olfaction: Effect of Uniqueness of the Initial Data and Information Coding on the Discrimination Ability of Multisensor Arrays
  in IEEE sensors journal
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Burlachenko JV, Snopok BA, Capone S, Siciliano P (literal)

Pagina inizio

• 649 (literal)

Pagina fine

• 656 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 11 (literal)

Rivista

• IEEE sensors journal (Rivista)

Note

• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• 1. Natl Acad Sci Ukraine, V Lashkaryov Inst Semicond Phys, UA-03028 Kiev, Ukraine 2. Italian Natl Council Res, Inst Microelect & Microsyst, I-73100 Lecce, Italy (literal)

Titolo

• Performance of Machine Olfaction: Effect of Uniqueness of the Initial Data and Information Coding on the Discrimination Ability of Multisensor Arrays (literal)

Abstract

• The optimization of a sensor array for a concrete analytical task is usually concerned with choosing a set of sensors to provide the best classification. In this work, a method for the prediction of the quality of classification by evaluation of the uniqueness of the raw experimental data is proposed. The key feature of the method is the presentation of the response of array as a function of the responses of its sensors. The dispersion of those functions serves as quantitative measure of uniqueness of the experimental data for a given set of analytes. The efficiency of the approach has been successfully demonstrated using both simulated and experimental data obtained from the array of three mass-sensitive sensors. The best conformity of the classification efficiency in cluster analysis with results obtained in the framework of the proposed approach is observed in the case of Langmuir-type adsorption processes. (literal)

Prodotto di

• Institute for microelectronics and microsystems (IMM) (Istituto)
• Sensori e Microsistemi Intelligenti per la Sicurezza e la Qualità della vita nei settori Agroalimentare, Trasporti ed \"Ambient Assisted Living\" (MD.P05.010.001) (Modulo)

Autore CNR

• SIMONETTA CAPONE (Persona)
• PIETRO ALEARDO SICILIANO (Unità di personale interno)

Incoming links:

Prodotto

• Institute for microelectronics and microsystems (IMM) (Istituto)
• Sensori e Microsistemi Intelligenti per la Sicurezza e la Qualità della vita nei settori Agroalimentare, Trasporti ed \"Ambient Assisted Living\" (MD.P05.010.001) (Modulo)

Autore CNR di

• SIMONETTA CAPONE (Persona)
• PIETRO ALEARDO SICILIANO (Unità di personale interno)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• IEEE sensors journal (Rivista)