• DocumentCode
    527501
  • Title

    Blind multi-valued signals detection using discrete Hopfield network

  • Author

    Zhang, Yun ; Zhang, Zhi-Yong

  • Author_Institution
    Coll. of Telecommun. & Inf. Eng., Nanjing Univ. of Posts & Telecommun., Nanjing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    1079
  • Lastpage
    1083
  • Abstract
    The conventional neural networks which are limited to two-state neurons are not able to solve the problem of blind multi-valued signal detection. A new algorithm based on discrete Hopfield neural network(DHNN) is proposed to detect multivalued signals blindly. A discrete 4-level signum-type activation function is constructed for 4PAM signals. For the blind signal detection, the optimization performance function is constructed and it does not rely on the second or higher order statistics of the received signals. Based on the new weight matrixes and the energy function of multi-value DHNN, the stability for multi-value DHNN is also proved in the paper. Simulation results show that the algorithm reach the real equilibrium points in a few iterations and show high speed to blindly detect multi-valued signals in stochastic channels.
  • Keywords
    Hopfield neural nets; blind source separation; iterative methods; matrix algebra; signal detection; stochastic processes; blind multivalued signals detection; discrete 4-level signum-type activation function; discrete Hopfield neural network; energy function; neural networks; optimization performance function; stochastic channels; weight matrix; Artificial neural networks; Bit error rate; Hopfield neural networks; Neurons; Signal detection; Signal to noise ratio; Simulation; Discrete hopfield neural network(DHNN); Multi-valued signals; blind detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583004
  • Filename
    5583004