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An attempt in modelling early intervention in autism using neural networks
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
2004 (English)In: Proceedings: Budapest, Hungary, 25 - 29 July 2004, Piscataway, NJ: IEEE Communications Society, 2004, 29-34 p.Conference paper (Refereed)
Abstract [en]

We present a solution to a problem of early intervention in autistic learning. This is an addition to our model of autism which is based on Kohonen self-organizing maps extended with the source familiarity filter and the attention shift mechanism. In particular we study the feature map formation when attention shift is restricted by familiarity preference. The network learns the stimuli from the source with the lowest variability in great detail at the expense of the other source. The early intervention neural controller modifies the probabilities of presenting stimuli from a given source in response to the attention shift acceptance/rejection signals.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2004. 29-34 p.
Research subject
Industrial Electronics
URN: urn:nbn:se:ltu:diva-39306DOI: 10.1109/IJCNN.2004.1379864Local ID: dfa92110-6f58-11db-962b-000ea68e967bISBN: 0-7803-8359-1OAI: diva2:1012816
IEEE International Joint Conference on Neural Networks : 25/06/2004 - 29/06/2004
Godkänd; 2004; 20060929 (ysko)Available from: 2016-10-03 Created: 2016-10-03Bibliographically approved

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Paplinski, AndrewGustafsson, Lennart
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