A theory of self-organising neural networks

The purpose of this paper is to present a probabilistic theory of self-organising networks based on the results published in [1]. This approach allows vector quantisers and topographic mappings to be treated as different limiting cases of the same theoretical framework. The full theoretical machinery allows a visual cortex-like network to be built.