• DocumentCode
    3628769
  • Title

    Univalent Neural Nets and Shape Detection

  • Author

    František Hakl

  • Author_Institution
    Inst. of Comput. Sci., Czech Acad. of Sci., Prague
  • fYear
    2007
  • Firstpage
    866
  • Lastpage
    875
  • Abstract
    We introduce a notion of so called univalent neural networks realizing injective mapping and sharing the input and output space. First, we postulate necessary and sufficient conditions of univalence and derive several models of univalent nets. Then explore learning algorithms that could be used for the defined network class - special variants of backpropagation learning.
  • Keywords
    "Artificial neural networks","Training","Classification algorithms","Matrix decomposition","Sufficient conditions","Linear matrix inequalities","Approximation algorithms"
  • Publisher
    ieee
  • Conference_Titel
    Signal-Image Technologies and Internet-Based System, 2007. SITIS ´07. Third International IEEE Conference on
  • Print_ISBN
    978-0-7695-3122-9
  • Type

    conf

  • DOI
    10.1109/SITIS.2007.126
  • Filename
    4618865
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3628769