• DocumentCode
    2682146
  • Title

    The non-stationary signal prediction by using quantum NN

  • Author

    Lee, Chang-Der ; Chen, Yu-Ju ; Huang, Huang-Chu ; Hwang, Rey-Chue ; Yu, Gwo-Ruey

  • Author_Institution
    Dept. Electr. Eng., I-Shou Univ., Kaohsiung, Taiwan
  • Volume
    4
  • fYear
    2004
  • fDate
    10-13 Oct. 2004
  • Firstpage
    3291
  • Abstract
    In this paper, the non-stationary power signal prediction by using quantum neural network (QNN) is proposed. The signals with fuzziness are expected to be classified clearly for enhancing the learning efficiency of neural network due to the hidden units with various graded levels in QNN structure. For a comparison, all experiments are also performed using the conventional neural network (CNN) structure.
  • Keywords
    learning (artificial intelligence); neural nets; prediction theory; quantum computing; signal detection; conventional neural network structure; learning algorithm; nonstationary signal prediction; quantum neural network; Cellular neural networks; Engineering management; Industrial engineering; Neural networks; Predictive models; Signal mapping; Signal processing; Signal processing algorithms; System identification; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2004 IEEE International Conference on
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-8566-7
  • Type

    conf

  • DOI
    10.1109/ICSMC.2004.1400848
  • Filename
    1400848