• DocumentCode
    2404568
  • Title

    Locally recurrent networks with multiple time-scales

  • Author

    Juan, Jui-Kuo ; Harris, John G. ; Principe, Jose C.

  • Author_Institution
    Comput. Neuro-Eng. Lab., Florida Univ., Gainesville, FL, USA
  • fYear
    1997
  • fDate
    24-26 Sep 1997
  • Firstpage
    645
  • Lastpage
    653
  • Abstract
    We introduce a new generalized feedforward structure that provides for multiple time scales. The gamma, Laguerre and other locally recurrent feedforward structures perform poorly in cases where widely varying time constants are required. By exponentially varying the time-constant along the delay line, a single delay line is able to represent signals that include various time scales. We demonstrate both discrete- and continuous-time versions of this multiple time-scale structure which we call the multi-scale gamma filter. The multi-scale gamma has a very natural implementation in sub-threshold CMOS and measured impulse responses from a continuous-time analog VLSI chip are shown
  • Keywords
    CMOS analogue integrated circuits; IIR filters; VLSI; continuous time filters; discrete time filters; feedforward neural nets; neural chips; recurrent neural nets; CMOS; analog VLSI chip; continuous-time filter; delay line; discrete time filter; feedforward neural networks; impulse responses; locally recurrent networks; multiple time-scales; multiscale gamma filter; Delay lines; Digital filters; Feedforward systems; Finite impulse response filter; Hardware; Laboratories; Measurement standards; Neural engineering; Semiconductor device measurement; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Signal Processing [1997] VII. Proceedings of the 1997 IEEE Workshop
  • Conference_Location
    Amelia Island, FL
  • ISSN
    1089-3555
  • Print_ISBN
    0-7803-4256-9
  • Type

    conf

  • DOI
    10.1109/NNSP.1997.622447
  • Filename
    622447