🚀 go-pugleaf

             Electrical Engineering Computer Group
                     Cider Seminar Series

       A Neural Network for Temporal Pattern Recognition

                              by
                           Tet Yeap
             Electrical Engineering Computer Group
                     University of Toronto

      Time: Tuesday, May 2, 1989, 12:05 --- Place: GB 220

       Recent work on neural networks has concentrated on their
  ability  to  store,  retrieve  and  process  static patterns.
  However,  in  problems  such  as  motion  detection,   speech
  processing  and predictive signal processing, the information
  to be processed consists of a sequence of temporally  related
  patterns.  Neural  networks  that handle only static patterns
  are not suited for these problems.

       A neural network that can  be  trained  to  recognize  a
  sequence  of  events in time is presented in this seminar. It
  utilizes  a  process  of  temporal  integration,   which   is
  implemented  by  providing each node with a fading memory and
  the use of a special interconnect pattern. A simulation model
  for  a  motion  detector  based  on  the proposed network was
  implemented.   It  can  be  trained  to  distinguish  between
  several speeds of a moving pattern of random dots.

                          Coming Soon

 Date         Who                        Topic

May 19   Prof. Wortman,   Adventures in Concurrent Compilation
         Michael Junkin


-- 
  Duncan Elliott, Dept. EE, University of Toronto, Toronto, Canada M5S 1A5
  dunc@eecg.toronto.edu  dunc@eecg.utoronto.ca  uunet!utai!eecg!dunc
  LAT: 43 39' 35.9"N  LON: 79 23' 41.7"W ELEVATION: 349.30          VE3PKD