An extended model on self-organizing map

Authors:
Shuzhong Yang;Siwei Luo;Jianyu Li
Affiliations:
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China;School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China;School of Computer and Software, Communication University of China, Beijing, China
Venue:
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Year:
2006

Citing 2
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Abstract

In this paper, we present an extended self-organizing map. It keeps full connectivity between adjacent layers but adds new virtual connections between neurons of competitive layer so that the structure of competitive layer can be regarded as a graph and can be expressed by an adjacent matrix. Thus, the conventional SOMs can be regarded as special cases of the extended model. Then we can evolve the graph into arbitrary topology such as small world graph and random graph. After evolution we can obtain arbitrary nonlinear neighborhood kernel of neurons and the obtained topology of competitive layer is expected to simulate the distribution of input samples. The experimental results show that the new extended model has better performance in speed and self-organization than conventional ones.