• DocumentCode
    1828997
  • Title

    Solving ability of Hopfield Neural Network with scale-rule noise for QAP

  • Author

    Tada, Yoshifumi ; Uwate, Yoko ; Nishio, Yoshifumi

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Tokushima Univ., Tokushima
  • fYear
    2008
  • fDate
    18-21 May 2008
  • Firstpage
    105
  • Lastpage
    108
  • Abstract
    One of the applications of neural network is solving combinatorial optimization problems. In our past study, the solving ability of the Hopfleld Neural Network with noise for quadratic assignment problem is investigated. However, even if we injected the noise to the network, the optimal solution cannot occasionally be found. In this study, we propose the method adding scale-rule noise to the Hopfleld Neural Network to achieve better performance. By computer simulations solving quadratic assignment problem, we evaluate the performance of the method.
  • Keywords
    Hopfield neural nets; mathematics computing; optimisation; Hopfield neural network; QAP; quadratic assignment problem; scale-rule noise; Chaos; Computer simulation; Hopfield neural networks; Logistics; Neural networks; Neurons; Noise level; Performance gain; Production facilities; Stochastic resonance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    978-1-4244-1683-7
  • Electronic_ISBN
    978-1-4244-1684-4
  • Type

    conf

  • DOI
    10.1109/ISCAS.2008.4541365
  • Filename
    4541365