• DocumentCode
    2356507
  • Title

    Chirality in neural network systems

  • Author

    Yoshida, Hitoaki ; Miura, Mamoru

  • Author_Institution
    Dept. of Comput. Sci., Iwate Univ., Morioka, Japan
  • fYear
    1994
  • fDate
    5-8 Dec 1994
  • Firstpage
    3
  • Lastpage
    7
  • Abstract
    The concept of chirality is introduced artificial neural network field separation methods of enantiomers. The separated chiral network shows a characteristic function in most cases, and the combination of the chiral subunits implements new functions
  • Keywords
    chirality; isomerism; neural nets; ANN field separation methods; artificial neural network; characteristic function; chirality; enantiomers; neural network systems; Artificial neural networks; Biomedical optical imaging; Chemicals; Chemistry; Intelligent networks; Mirrors; Neural networks; Neurons; Optical computing; Proteins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1994. APCCAS '94., 1994 IEEE Asia-Pacific Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    0-7803-2440-4
  • Type

    conf

  • DOI
    10.1109/APCCAS.1994.514514
  • Filename
    514514
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2356507