• DocumentCode
    2337641
  • Title

    A novel chaotic neural networks and application

  • Author

    Shi, Wei-Feng ; Xue, Shi-Long

  • Author_Institution
    Dept. of Electri. Autom., Shanghai Maritime Univ., China
  • Volume
    8
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    4651
  • Abstract
    To increase ability of modeling and identification for nonlinear system by neural networks, the characteristics of neurons, learning rule and configuration of networks are researched. The chaotic neuron is introduced to neural networks to form local recurrent chaotic neural networks. The information treatment quantity of the networks is all so increased because there are feed back loops with recurrent networks. The local recurrent chaotic neural networks are used for a marine synchronous generator modeling with a marine real time simulator. In the networks training of generator modeling, a dynamic BP learning algorithm is applied. Compare to other neural networks modeling, the neuron number of hidden layer of the networks is few, the ability of generalization of the chaotic networks system is well.
  • Keywords
    backpropagation; marine engineering; nonlinear systems; power systems; recurrent neural nets; synchronous generators; chaotic neuron; dynamic BP learning algorithm; feed back loops; marine real time simulator; marine synchronous generator modeling; nonlinear system identification; recurrent chaotic neural network; Artificial neural networks; Bifurcation; Cellular neural networks; Chaos; Digital signal processing; Logistics; Neural networks; Neurons; Power system modeling; Recurrent neural networks; BP learning algorithm; Chaotic neural networks; modeling; neuron; recurrent networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527759
  • Filename
    1527759