Analysis of the convergency of topology preserving neural networks on learning

Abstract

In this paper, a general conclusion for verifying the convergency of topology preserving neural networks is presented, by which the networks are proven to produce convergent feature maps for uniformly distributed inputs. As a special example, the Kohonen’s self organizing networks are also proven to be convergent. This paper revises and extends the products in existance and provids a new method for further studying the convergence properties of self organizing neural networks.