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Neuron splitting for efficient feature map formation

By Lachlan L. H. Andrew

Abstract

Kohonen's Self Organizing Feature Map (SOFM) produces an ordered mapping from one space to another. This paper describes an algorithm inspired by the splitting initialization for the classical LBG method for vector quantizer design, which allows the efficient generation of maps with various topologies and with high local and global ordering

Topics: Algorithms, Classical LEG method, Computational complexity, Feature map formation, Global ordering, Kohonen Self Organising Feature Map, Local ordering, Mathematical models, Neural networks, Neuron splitting, Neuron splitting, Ordered mapping, Probability density function, Self organising feature map, SOFM, Splitting initialisation, Unsupervised learning, Vector quantisation, Vector quantiser design, Vectors
Publisher: IEEE
Year: 1994
DOI identifier: 10.1109/ANZIIS.1994.396960
OAI identifier: oai:vtl.cc.swin.edu.au:swin:10268
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