Liu, Xinhe 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. [Continues.] Nonlinear dynamics;Learning;Neural networks;Moment-based approximation;Mathematical Sciences not elsewhere classified 2015-11-19
    https://repository.lboro.ac.uk/articles/thesis/Implementation_of_dynamical_systems_with_plastic_self-organising_velocity_fields/9375905