• DocumentCode
    3116121
  • Title

    LogiCook and QUESTAR: two case studies in successful technology transfer

  • Author

    Tarassenko, L.

  • Author_Institution
    Oxford Univ., UK
  • fYear
    1997
  • fDate
    35473
  • Firstpage
    42370
  • Abstract
    Neural networks are ideally suited to the processing of noisy or uncertain data as they operate within a probabilistic framework. They produce probability estimates at their output and so allowance must be made for this. This is a very important consideration in the context of industrial applications and the author illustrates how this issue was addressed in the Sharp LogiCook (a neural network microwave oven) and in Oxford Medical´s QUESTAR (a neural network system for the analysis of sleep disorders)
  • Keywords
    ovens; Oxford Medical QUESTAR; Sharp LogiCook; industrial applications; neural network microwave oven; neural networks; noisy data processing; probabilistic framework; probability estimates; sleep disorder analysis; technology transfer; uncertain data processing;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Neural Networks for Industrial Applications (Digest No. 1997/014), IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19970099
  • Filename
    600730