• DocumentCode
    2768160
  • Title

    Comparative Study of Different Types of Wavelet Functions in Neural Network

  • Author

    Azeem, M.F. ; Banakar, Ahmad ; Kumar, Vinod

  • Author_Institution
    Aligarh Muslim Univ., Aligarh
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1061
  • Lastpage
    1066
  • Abstract
    Based on the wavelet transform theory, the new notion of the wavelet network is proposed as an alternative to feed forward neural networks for approximating arbitrary nonlinear functions. Boubez employed ortho-normal wavelets; Yamakawa, Uchino and Samatsu proposed two types of new neuron models and named Wavelet Synapse (WS) neuron and Wavelet Activation (WA) function neuron. These models are obtained by modifying the Mc Culloch and Pitts neuron model with non-orthogonal wavelet bases. Comparative study of different type of Wavelet functions is carried out in this paper by applying above two neuron models.
  • Keywords
    feedforward neural nets; function approximation; nonlinear functions; wavelet transforms; feed forward neural network; nonlinear function approximation; nonorthogonal wavelet function; wavelet activation function neuron model; wavelet synapse neuron model; wavelet transform theory; Continuous wavelet transforms; Educational institutions; Intelligent networks; Neural networks; Neurons; Performance analysis; Signal analysis; Signal resolution; Wavelet analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246806
  • Filename
    1716217