• DocumentCode
    2664249
  • Title

    A hierarchical neural network for temporal pattern recognition

  • Author

    Yeap, T.H. ; Zaky, S.G. ; Tsotsos, J.K. ; Kwan, H.C.

  • Author_Institution
    Toronto Univ., Ont., Canada
  • fYear
    1990
  • fDate
    1-3 May 1990
  • Firstpage
    2967
  • Abstract
    A hierarchical neural network that can be trained to recognize multiple sequences of temporal events is presented. The network modules are suitable for VLSI implementation. A motion detector based on a hierarchical network was simulated and tested. The simulation results show that modules can be concatenated to recognize a long temporal sequence. Results also show that modules at higher levels in the hierarchy can be trained to recognize the temporal order of the sequences presented to modules in the lower levels. The network can be used for temporal recognition of a number of long sequences
  • Keywords
    VLSI; learning systems; neural nets; pattern recognition; VLSI implementation; hierarchical neural network; long temporal sequence; motion detector; multiple sequences; network modules; temporal events; temporal pattern recognition; training; Computational modeling; Computer science; Concatenated codes; Detectors; Motion detection; Neural networks; Pattern recognition; Physiology; Testing; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1990., IEEE International Symposium on
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/ISCAS.1990.112633
  • Filename
    112633