• DocumentCode
    661263
  • Title

    Sound quality indicating system using EEG and GMDH-type neural network

  • Author

    Nishimura, Kosuke ; Mitsukura, Yasue

  • Author_Institution
    Dept. of Syst. Design Eng., Keio Univ., Yokohama, Japan
  • fYear
    2013
  • fDate
    Oct. 29 2013-Nov. 1 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper, we propose a sound quality evaluation system using electroencephalogram (EEG) and group method of data handling (GMDH) type neural network. Recently, EEG is used in various applications, and we focus on sound quality evaluation using EEG. We prepared EEG samples to train a GMDH-type neural network to recognise 3 typical types of sound which was used to create the training data. The results showed that using GMDH-type neural network improved recognition rate compared to the other method. Additionally, we repeated simulations by using different parameter of GMDH-type neural network, and the open test results showed the recognition rate variations in different parameter values.
  • Keywords
    data handling; electroencephalography; medical signal processing; neural nets; EEG-type neural network; GMDH-type neural network; electroencephalogram; group method of data handling; recognition rate; recognition rate variations; sound quality evaluation; sound quality evaluation system; sound quality indicating system; Biological neural networks; Electroencephalography; Feature extraction; Loudspeakers; Neurons; Principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific
  • Conference_Location
    Kaohsiung
  • Type

    conf

  • DOI
    10.1109/APSIPA.2013.6694124
  • Filename
    6694124