• DocumentCode
    2538760
  • Title

    System Identification of TP Film Evaporation by Using Nearly Equivalent NN Model

  • Author

    Huang, Du-Jou ; Huang, Chih-Chien ; Chen, Yu-Ju ; Huang, Huang-Chu ; Chen, Shen-Whan ; Hwang, Rey-Chue

  • Author_Institution
    Electr. Eng. Dept., I-Shou Univ., Kaohsiung, Taiwan
  • fYear
    2010
  • fDate
    13-15 Dec. 2010
  • Firstpage
    118
  • Lastpage
    121
  • Abstract
    This paper presents a technique, called “nearly equivalent neural network (NN) model” in the application of nonlinear system identification. This technique is expected to adequately to catch the behavior of the nonlinear system. To demonstrate the new technique proposed, the evaporation system of TP decoration film was analyzed. The complex relationship between the film´s transmittance and its possible influencing factors was identified. For the comparison, the same simulations were also performed by using the conventional neural network with the standard steepest descent error back-propagation (BP) learning algorithm.
  • Keywords
    identification; neural nets; nonlinear systems; thin films; touch sensitive screens; vacuum deposition; TP decoration film; error backpropagation learning algorithm; evaporation system; film transmittance; nearly equivalent neural network model; nonlinear system identification; Artificial neural networks; Mathematical model; Neurons; Optimization; Polynomials; System identification; Training; nearly equivalent neural network; system identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-8891-9
  • Electronic_ISBN
    978-0-7695-4281-2
  • Type

    conf

  • DOI
    10.1109/ICGEC.2010.37
  • Filename
    5715385