• DocumentCode
    2790292
  • Title

    A novel chaotic neural network with Morlet-wavelet activation function

  • Author

    Zhang, Jia-hai ; Sun, Shu-fang

  • Author_Institution
    Coll. of Electr. & Autom. Eng., Sanjiang Univ., Nanjing, China
  • fYear
    2011
  • fDate
    15-17 July 2011
  • Firstpage
    29
  • Lastpage
    32
  • Abstract
    The new model can solve the 10-city traveling salesman problem more effectively because of Morlet wavelet being a kind of basic function. First, the chaotic dynamics of the neuron was analyzed, and the figures of the reversed bifurcation and the maximal Lyapunov exponents of single neural unit were given. Second, the new model was applied to solve function optimizations and the evolution figures of the energy function were plotted. Finally, 10-city traveling salesman problem was given and simultaneously a group of parameters for the network in solving the 10-city traveling salesman problem were proved to be efficient by the computer simulation. Seen from the simulation results, the new model is powerful.
  • Keywords
    Lyapunov methods; bifurcation; chaos; digital simulation; neural nets; travelling salesman problems; Morlet-wavelet activation function; chaotic neural network; computer simulation; function optimizations; maximal Lyapunov exponents; neuron chaotic dynamics; reversed bifurcation; ten-city traveling salesman problem; Bifurcation; Biological neural networks; Chaos; Cities and towns; Neurons; Optimization; Activation Function; Chaotic; Morlet-Wavelet; Neural Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on
  • Conference_Location
    Hohhot
  • Print_ISBN
    978-1-4244-9436-1
  • Type

    conf

  • DOI
    10.1109/MACE.2011.5986849
  • Filename
    5986849