We consider a case of self-organization in which a relatively small number N of data points is mapped on a larger number M of nodes. This is a reverse situation to a typical clustering problem when a node represents a center of the cluster of data points. In our case the objective is to have a Gaussian-like distribution of weights over nodes in the neighbourhood of the winner for a given stimulus. The fact that M > N creates some problem with using learning schemes related to Gaussian MixtureModels.We also show how the objects, Chinese characters in our case, can be topologically ordered on a surface of a 3D sphere. A Chinese character is represented by an angular integral of the Radon Transform (aniRT) which is an RTS-invariant 1-D signature function of an image.
CITATION STYLE
Papliński, A. P. (2016). Self-organization on a sphere with application to topological ordering of chinese characters. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9950 LNCS, pp. 452–459). Springer Verlag. https://doi.org/10.1007/978-3-319-46681-1_54
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