• DocumentCode
    295748
  • Title

    Computational neural networks

  • Author

    Yang, Jar-Ferr ; Chen, Chi-Ming

  • Author_Institution
    Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • Volume
    3
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    1249
  • Abstract
    In this paper, we discuss an approach for designing the computational neural network, which is mainly composed of a hardlimiter neuron, a updated neuron, and a search function neuron, to solve some computational problems. The computation-by-search scheme can effectively solve some complicated problems in the condition that their search functions can be easily obtainable by some existing neural networks. The convergence of the suggested neural networks to achieve the solution are discussed and analyzed. Both theoretical analyses and simulated results show that the proposed neural network can effectively solve the complicated computational problems such that they belong to the rational functions or their inverse functions can be easily implemented by using an existing network
  • Keywords
    convergence of numerical methods; functional analysis; iterative methods; mathematics computing; neural nets; search problems; computation-by-search scheme; computational neural network; convergence; hardlimiter neuron; inverse functions; rational functions; search function neuron; updated neuron; Analog circuits; Analog computers; Analytical models; Computational modeling; Computer networks; Integrated circuit interconnections; Neural networks; Neurons; Pattern classification; Quadratic programming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.487334
  • Filename
    487334