• DocumentCode
    2748308
  • Title

    Wavelet Neural Network-based Control Chart Patterns Recognition

  • Author

    Wu, Shaoxiong ; Wu, Biying

  • Author_Institution
    Dept. of Econ. & Manage., Fujian Univ. of Technol., Fuzhou
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    9718
  • Lastpage
    9721
  • Abstract
    As for six patterns of control chart, wavelet neural network was presented. The structure of wavelet neural network was made up of three-layer network, of which there were 24 neurons of input layer, 20 neurons of hidden layer as well as 6 neurons of output layer. Mexican Hat wavelet was selected as activation function. The simulation results show that wavelet neural network have many advantages, such as quicker training and better recognition performance and better convergence than BP networks, which can be used in control chart recognition
  • Keywords
    control charts; neural nets; pattern recognition; wavelet transforms; Mexican hat wavelet; activation function; control chart pattern recognition; wavelet neural network; Artificial neural networks; Automatic control; Computer integrated manufacturing; Control charts; Convergence; Expert systems; Neural networks; Neurons; Pattern recognition; Quality control; Control chart; pattern recognition; wavelet neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1713890
  • Filename
    1713890