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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/19550

Title: Implementation of dynamical systems with plastic self-organising velocity fields
Authors: Liu, Xinhe
Keywords: Nonlinear dynamics
Learning
Neural networks
Moment-based approximation
Issue Date: 2015
Publisher: © Xinhe Liu
Abstract: 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. [Continues.]
Description: A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.
URI: https://dspace.lboro.ac.uk/2134/19550
Appears in Collections:PhD Theses (Maths)

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