• DocumentCode
    3442371
  • Title

    MAN: mass attraction network

  • Author

    Erdem, Mahmut Hilmi ; Ozturk, Yusuf

  • Author_Institution
    Dept. of Comput. Eng., Ege Univ., Izmir, Turkey
  • Volume
    6
  • fYear
    1994
  • fDate
    30 May-2 Jun 1994
  • Firstpage
    455
  • Abstract
    In this study, a binary associative memory, inspired from Newton´s mass attraction theory is proposed and some related analysis is given. In the model, memory items are considered as masses in the interior or at the corners of a hypercube. In recall, “attraction forces” are computed and the memory item, whose “force” is the greatest, becomes the output pattern. Since the operation of the model is highly parallel, the network is extremely fast. Retrieving a memory item takes only two steps. The proposed model has been observed to be superior to Hamming net, Hopfield network and Harmony theory in various aspects
  • Keywords
    content-addressable storage; learning (artificial intelligence); neural nets; parallel processing; MAN; attraction forces; binary associative memory; hypercube; mass attraction network; output pattern; parallel operation; Associative memory; Computational modeling; Computer simulation; Cost function; Equations; Gravity; Hamming distance; Information theory; Pattern analysis; Simulated annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on
  • Conference_Location
    London
  • Print_ISBN
    0-7803-1915-X
  • Type

    conf

  • DOI
    10.1109/ISCAS.1994.409624
  • Filename
    409624