• DocumentCode
    1749401
  • Title

    Detection and identification of odorants using an electronic nose

  • Author

    Polikar, Robi ; Shinar, Ruth ; Honavar, Vasant ; Udpa, Lalita ; Porter, Marc D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Rowan Univ., Glassboro, NJ, USA
  • Volume
    5
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    3137
  • Abstract
    Gas sensing systems for detection and identification of odorant molecules are of crucial importance in an increasing number of applications. Such applications include environmental monitoring, food quality assessment, airport security, and detection of hazardous gases. We describe a gas sensing system for detecting and identifying volatile organic compounds (VOC), and discuss the unique problems associated with the separability of signal patterns obtained by using such a system. We then present solutions for enhancing the separability of VOC patterns to enable classification. A new incremental learning algorithm that allows new odorants to be learned is also introduced
  • Keywords
    gas sensors; learning (artificial intelligence); pollution control; signal classification; Gas sensing systems; classification; detection odorant molecules; identification odorant molecules; incremental learning algorithm; separability VOC patterns; volatile organic compounds; Acoustic signal detection; Airports; Application software; Chemical sensors; Electronic noses; Gas detectors; Gases; Landmine detection; Polymer films; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
  • Conference_Location
    Salt Lake City, UT
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7041-4
  • Type

    conf

  • DOI
    10.1109/ICASSP.2001.940323
  • Filename
    940323