• DocumentCode
    1987812
  • Title

    A fuzzy logic based neural network classifier for qualitative classification of odors/gases

  • Author

    Kumar, Ravi ; Das, R.R. ; Mishra, V.N. ; Dwivedi, R.

  • Author_Institution
    Dept. of Electron. Eng., Banaras Hindu Univ., Varanasi, India
  • fYear
    2009
  • fDate
    22-24 Dec. 2009
  • Firstpage
    185
  • Lastpage
    188
  • Abstract
    This paper presents a novel approach to odor discrimination using data obtained from the responses of thick film tin oxide sensor array fabricated at our laboratory and employing backpropagation algorithm trained artificial neural network based on fuzzy logic. Fuzzy membership values were used as target vectors to the proposed neural classifier. Three different versions of backpropagation algorithm were used to train the network and their performances have been compared. Superior learning and classification performance was obtained using proposed model trained with TRAINLM version of the backpropagation algorithm.
  • Keywords
    backpropagation; computerised instrumentation; electronic noses; fuzzy logic; fuzzy neural nets; intelligent sensors; pattern classification; sensor arrays; signal processing equipment; TRAINLM; backpropagation algorithm; fuzzy logic based neural network classifier; gas qualitative classification; odor discrimination; odor qualitative classification; thick film tin oxide sensor array; trained artificial neural network; Artificial neural networks; Backpropagation algorithms; Fuzzy logic; Gases; Logic arrays; Neural networks; Sensor arrays; Thick film sensors; Thick films; Tin; algorithm; electronic nose; fuzzy logic; intelligent gas sensor; microsensors; neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Trends in Electronic and Photonic Devices & Systems, 2009. ELECTRO '09. International Conference on
  • Conference_Location
    Varanasi
  • Print_ISBN
    978-1-4244-4846-3
  • Type

    conf

  • DOI
    10.1109/ELECTRO.2009.5441140
  • Filename
    5441140