• DocumentCode
    2871531
  • Title

    Recognition of effective algorithm using a higher order multi-layer neural networks

  • Author

    Junwen, Gao ; Jiancheng, Liu

  • Author_Institution
    Electron. Dept., Guangdong Agric.-Ind.-Bus. Polytech. Coll., Guangzhou, China
  • Volume
    9
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    A new neural network architecture, call a higher order multi-layer neural networks(HOMLNN) is presented. The architecture of an HOMLNN is a modified model of the Evolved functional neural network(EFNN)with a hidden layer which is composed of self-evolve neurons and additional multiplication inputs between conventional inputs and self-evolve neurons. The authors drive a generalized dynamic backpropagation algorithm and show a new approach to the Recognition of dynamical systems by means of HOMLNN. Experiment result showed that the method is effective for the Recognition of dynamical systems.
  • Keywords
    backpropagation; neural nets; EFNN; HOMLNN; dynamic backpropagation algorithm; effective algorithm recognition; evolved functional neural network; higher order multilayer neural networks; self evolve neurons; Artificial neural networks; Delay; Equalizers; Feedforward neural networks; Heuristic algorithms; Neurons; Nonlinear dynamical systems; Algorithm; dynamical systems; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5623052
  • Filename
    5623052