• DocumentCode
    1818120
  • Title

    Implementing competitive learning in a quantum system

  • Author

    Ventura, Dan

  • Author_Institution
    Fonix Corp., Salt Lake City. UT, USA
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    462
  • Abstract
    Ideas from quantum computation are applied to the field of neural networks to produce competitive learning in a quantum system. The resulting quantum competitive learner has a prototype storage capacity that is exponentially greater than that of its classical counterpart. Furthermore, empirical results from simulation of the quantum competitive learning system on real-world data sets demonstrate the quantum system´s potential for excellent performance
  • Keywords
    neural nets; pattern classification; quantum theory; unsupervised learning; competitive learning; neural networks; pattern classification; quantum system; storage capacity; Computational modeling; Computer networks; Hilbert space; Learning systems; Neural networks; Prototypes; Quantum computing; Quantum mechanics; Vectors; Wave functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.831539
  • Filename
    831539