• DocumentCode
    1151846
  • Title

    Discrete-Time Recurrent Neural Networks With Complex-Valued Linear Threshold Neurons

  • Author

    Zhou, Wei ; Zurada, Jacek M.

  • Author_Institution
    Comput. Intell. Lab., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • Volume
    56
  • Issue
    8
  • fYear
    2009
  • Firstpage
    669
  • Lastpage
    673
  • Abstract
    This brief discusses a class of discrete-time recurrent neural networks with complex-valued linear threshold neurons. It addresses the boundedness, global attractivity, and complete stability of such networks. Some conditions for those properties are also derived. Examples and simulation results are used to illustrate the theory.
  • Keywords
    complex networks; electronic engineering computing; network synthesis; recurrent neural nets; stability; boundedness; complex-valued linear threshold neurons; discrete-time recurrent neural networks; global attractivity; network stability; Complex-valued neural networks (NNs); discrete-time recurrent neural networks (RNNs); linear threshold (LT);
  • fLanguage
    English
  • Journal_Title
    Circuits and Systems II: Express Briefs, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1549-7747
  • Type

    jour

  • DOI
    10.1109/TCSII.2009.2025625
  • Filename
    5175325
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1151846