• DocumentCode
    3695559
  • Title

    Hierarchical encoding of human working memory

  • Author

    Guoqi Li;Jing Pei;Changyun Wen;Zhengguo Li;Guangshe Zhao;Luping Shi

  • Author_Institution
    Center for Brain Inspired Research (CBICR), Department of Precision Instrument, Tsinghua University, Beijing, China, 100084
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    866
  • Lastpage
    871
  • Abstract
    A model for encoding and the retrieve of the sequential working memory is proposed by using bidirectional inhibition-connected neural networks with winnerless competition. It is found that the retrieve accuracy is dependent on the encoding time the the properties of the neural inhibition weights. The simulation results shows the effectiveness of our proposed model.
  • Keywords
    "Neurons","Mathematical model","Predator prey systems","Encoding","Psychology","Analytical models","Biological neural networks"
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on
  • Type

    conf

  • DOI
    10.1109/ICIEA.2015.7334232
  • Filename
    7334232
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3695559