• DocumentCode
    3594455
  • Title

    The iterative identification method for hammerstein nonlinear channel

  • Author

    Rui Su ; Bin Wang ; Shigang Liu

  • fYear
    2014
  • Firstpage
    67
  • Lastpage
    72
  • Abstract
    This paper is concerned with the iteration identification algorithm for Hammerstein model with complex-valued input for the fact that the existing algorithms are not valid for complex input. Based on the stochastic gradient algorithm, the extended stochastic gradient algorithm is proposed by defining new cost function for complex input. The extended hierarchical multi-innovation stochastic gradient algorithm is proposed by introducing multi-innovation identification theory and hierarchical principle to the extended stochastic gradient algorithm. Experimental simulations show that the extended hierarchical multi-innovation stochastic gradient algorithm has better performance than the extended stochastic gradient algorithm at the expense of computational complexity.
  • Keywords
    gradient methods; identification; iterative methods; stochastic processes; wireless channels; Hammerstein nonlinear channel; complex-valued input; computational complexity; cost function; extended hierarchical multiinnovation stochastic gradient algorithm; iterative identification method; multiinnovation identification theory; Hammerstein Model; Hierarchical; Iterative Identification; Multi-Innovation; Stochastic Gradient Algorithm;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing (WiCOM 2014), 10th International Conference on
  • Print_ISBN
    978-1-84919-845-5
  • Type

    conf

  • DOI
    10.1049/ic.2014.0075
  • Filename
    7129603