• DocumentCode
    2938222
  • Title

    Antenna recognition based on BP neural network

  • Author

    Chunyan Zhao ; Dan Shi ; Yougang Gao

  • Author_Institution
    Sch. of Electron. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2012
  • fDate
    6-9 Nov. 2012
  • Firstpage
    355
  • Lastpage
    359
  • Abstract
    This paper studies several commonly used algorithms in the BP neural network. Training the BP neural network under these different algorithms can see the various performance of their networks. The study of both classical BP algorithm and LM algorithm will find the improvements of LM algorithm. In addition, practical applications show the following two things. For one hand, different BP algorithm impacts the speed of the network. For the other, the number of hidden layer neurons is also a sensitive factor to the performance of BP neural network. On the basis of the BP neural network, we want to build a suitable antenna model and use it in the identification of the antennas, it will have great practical significance.
  • Keywords
    antennas; backpropagation; neural nets; radiocommunication; BP neural network; LM algorithm; antenna recognition; Algorithm design and analysis; Biological neural networks; Microwave antennas; Neurons; Standards; Training; BP neural network; LM algorithm; classic BP algorithm; hidden layer nodes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Environmental Electromagnetics (CEEM), 2012 6th Asia-Pacific Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-0030-8
  • Type

    conf

  • DOI
    10.1109/CEEM.2012.6410642
  • Filename
    6410642