• DocumentCode
    1375988
  • Title

    Neural network approach for solving the maximal common subgraph problem

  • Author

    Shoukry, Amin ; Aboutabl, Mohamed

  • Author_Institution
    Dept. of Comput. Sci., Alexandria Univ., Egypt
  • Volume
    26
  • Issue
    5
  • fYear
    1996
  • fDate
    10/1/1996 12:00:00 AM
  • Firstpage
    785
  • Lastpage
    790
  • Abstract
    A new formulation of the maximal common subgraph problem (MCSP), that is implemented using a two-stage Hopfield neural network, is given. Relative merits of this proposed formulation, with respect to current neural network-based solutions as well as classical sequential-search-based solutions, are discussed
  • Keywords
    Hopfield neural nets; computer vision; information retrieval; pattern recognition; search problems; classical sequential-search-based solutions; maximal common subgraph problem; neural network approach; two-stage Hopfield neural network; Annealing; Hopfield neural networks; Information processing; Intelligent structures; Magnetic materials; Neural networks; Neurons; Pattern matching; Pattern recognition; Temperature;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/3477.537320
  • Filename
    537320