• DocumentCode
    1744932
  • Title

    The variable neighborhood CNN

  • Author

    Namba, M. ; Takatori, S. ; Kawabata, H. ; Zhang, Z.

  • Author_Institution
    Fac. of Comput. Sci. & Syst. Eng., Okayama Prefectural Univ., Japan
  • Volume
    3
  • fYear
    2001
  • fDate
    6-9 May 2001
  • Firstpage
    105
  • Abstract
    The cellular neural network (CNN) has been widely used for associative memory. However, it has a problem called indeterminate cell. We describe this problem and propose the variable neighborhood CNN. As a result, we have been able to avoid the problem, and construct a more efficient CNN system for associative memory in simulation
  • Keywords
    cellular neural nets; content-addressable storage; singular value decomposition; SVD; algorithm searching; associative memory; computation time; indeterminate cell problem; memory patterns; stable equilibrium points; variable neighborhood CNN; Analog circuits; Cellular neural networks; Circuit noise; Computer science; Equations; Feature extraction; Liver diseases; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    0-7803-6685-9
  • Type

    conf

  • DOI
    10.1109/ISCAS.2001.921257
  • Filename
    921257
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1744932