Thesis-2015-Liu.pdf (11.28 MB)
Implementation of dynamical systems with plastic self-organising velocity fields
thesis
posted on 2015-11-19, 17:01 authored by Xinhe LiuTo 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.]
History
School
- Science
Department
- Mathematical Sciences
Publisher
© Xinhe LiuPublisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2015Notes
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.Language
- en