Summary
International Symposium on Nonlinear Theory and Its Applications
2016
Session Number:B2L-C
Session:
Number:B2L-C-4
Clustered Multidimensional Scaling with Rulkov Neurons
Thomas Ott, Martin Schule, Jenny Held, Carlo Albert, Ruedi Stoop,
pp.-
Publication Date:2016/11/27
Online ISSN:2188-5079
Summary:
We present a method for mapping high-dimensional fast visual interpretation. In order to correctly grasp cluster structures in high-dimensional situations, we combine classical multi-dimensional scaling with data clustering based on self-organization processes in networks of Rulkov neurons. The goal of our approach is to amplify rather than preserve local cluster structures. We report on an implementation of the method with Rulkov-Hebbian-learning clustering and illustrate its suitability in comparison to traditional methods by means of an artificial dataset and a real world example.