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A growing parallel self-organizing map for unsupervised learning
Conference proceeding

A growing parallel self-organizing map for unsupervised learning

I. Valova, D. Szer, N. Georgieva and IEEE
Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290), Vol.2, pp.1924-1929 vol.2
2002
DOI: https://doi.org/10.1109/IJCNN.2002.1007813

Abstract

Computer networks Computer science Counting circuits Distributed computing Educational institutions Euclidean distance Information science Network topology Neural networks Unsupervised learning
SOM approximates a high dimensional unknown input distribution with lower dimensional neural network structure to model the topology of the input space as closely as possible. We present a SOM that processes the whole input in parallel and organizes itself over time. This way, networks can be developed that do not reorganize their structure from scratch every time a new set of input vectors is presented but rather adjust their internal architecture in accordance with previous mappings.

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