• DocumentCode
    328917
  • Title

    Weighting function in neural network

  • Author

    Zhang, Yongjun ; Chen, Zongahi

  • Author_Institution
    Inst. of Electron., Acad. Sinica, Beijing, China
  • Volume
    2
  • fYear
    1993
  • fDate
    25-29 Oct. 1993
  • Firstpage
    1454
  • Abstract
    The recurrent correlation neural networks have high-capacity associative memory when the weighting function satisfies certain condition. But this always causes the high dynamics in the neural network and the hardware realization is difficult. This paper gives the relationship between the capacity and dynamics and provides a general principle for the choice of the weighting function and give a kind of weighting function. It has high-capacity and avoids the high dynamics. Finally, the simulated results are given.
  • Keywords
    content-addressable storage; correlation theory; recurrent neural nets; high-capacity associative memory; recurrent correlation neural networks; weighting function; Biological neural networks; Equations; Identity-based encryption; Intelligent networks; Neural network hardware; Neural networks; Neurons; Recurrent neural networks; State estimation; Tellurium;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
  • Print_ISBN
    0-7803-1421-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.1993.716819
  • Filename
    716819