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Implementation of dynamical systems with plastic self-organising velocity fields

To describe learning, as an alternative to a neural network recently dynamical systems were introduced whose vector fields were plastic and self-organising. Such a system automatically modifies its velocity vector field in response to the external stimuli. In the simplest case under certain conditions its vector field develops into a gradient of a multi-dimensional probability density distribution of the stimuli. We illustrate with examples how such a system carries out categorisation, pattern recognition, memorisation and forgetting without any supervision.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:713657
Date January 2015
CreatorsLiu, Xinhe
PublisherLoughborough University
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttps://dspace.lboro.ac.uk/2134/19550

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