• DocumentCode
    3081041
  • Title

    A Research on Automatic Modulation Recognition with the Combination of the Rough Sets and Neural Network

  • Author

    Wang, Hua-Kui ; Zhang, Bin ; Wu, Juan-Ping ; Han, Ying-Zheng ; Wu, Xiao-Wei ; Jia, Ruo-Si

  • Author_Institution
    Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
  • fYear
    2010
  • fDate
    17-19 Sept. 2010
  • Firstpage
    807
  • Lastpage
    810
  • Abstract
    Automatic modulation recognition of modulation signals is the key problem in non-cooperative communication systems. The method which combines the rough set theory and the neural network is designed for identifying the six modulation types based on the research on the feature set of digital modulation recognition. Simulation results show that the new method simplifies the structure of neural networks and decreases the training time without reducing the recognition rate.
  • Keywords
    modulation; neural nets; rough set theory; signal detection; automatic modulation recognition; digital modulation recognition; modulation signals; neural network; noncooperative communication system; rough set combination; rough set theory; Artificial neural networks; Digital modulation; Feature extraction; Rough sets; Training; automatic modulation recognition; neural network; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4244-8043-2
  • Electronic_ISBN
    978-0-7695-4180-8
  • Type

    conf

  • DOI
    10.1109/PCSPA.2010.201
  • Filename
    5635540