Path: utzoo!utgpu!news-server.csri.toronto.edu!cs.utexas.edu!swrinde!zaphod.mps.ohio-state.edu!uakari.primate.wisc.edu!uflorida!stat!kerce From: kerce@nu.cs.fsu.edu (Kingsley F. Kerce) Newsgroups: comp.ai.neural-nets Subject: Re: Learning of Temporal Patterns with Neural Networks Message-ID: Date: 21 Mar 90 05:07:45 GMT References: <893@xenon.kcl-cs.UUCP> Sender: news@stat.fsu.edu Organization: Florida State University Computer Science Lines: 32 In-reply-to: guy@kcl-cs.UUCP's message of 19 Mar 90 15:24:58 GMT [Email to guy@kcl-cs.UUCP bounced.] Here's some references from a tutorial I attended during the WNN-AIND 1990 workshop. Grossberg, Stephen. "Some networks can learn, remember, and reproduce any number of complicated space-time patterns", Journal of Math. and Mechanics #19, pp. 53-91, 196?. (unsure of the year) Hecht-Nielsen. "Nearest matched filter classification of spatio-temporal patterns", Applied Optics #26, pp. 1892-1899, 1987. Ito and Fukushima. "Recognition of spatio-temporal patterns with a hierarchical neural network", Proc. of IJCNN 1990 #1, pp. 273-276, 1990. Fukushima. "Spatio-temporal vs. spatial pattern recognition by neocognitron", Proc. of IJCNN 90 #2, pp. 279-282, 1990. Waibel, Hanazawa, Hinton, Shikano, and Lang. "Phoneme recognition using time-delay neural networks", IEEE Trans. ASSP #37, pp. 328-339, 1989. Hope this is actually what you're after. Note that I'm not particularly interested in the above references--I just recalled running across them in the tutorial. Good luck, -- Kingsley Kerce USnail: Dept. of Computer Sci. (or Dept. of Psych.) Email: kerce@nu.cs.fsu.edu Florida State University Work Phone: (904) 644-5436 Tallahassee, FL 32306