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.]
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.