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Authors: A. V. Novikov and E. N. Benderskaya

Affiliation: St.-Petersburg State Polytechnical University, Russian Federation

Keyword(s): Cluster Analysis, Kuramoto Model, Self-organized Feature Map, Oscillatory Network.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Clustering ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: Despite partial synchronization in the oscillatory networks based on Kuramoto model can be used for cluster analysis, convergence rate of synchronization processes depends on number of oscillators and number of links between oscillators. Moreover result of clustering depends on radius of connectivity that should be chosen in line with input data. We propose double-layer oscillatory network for the two problems. Our network relevant in situation when fast solution is required and when input data should be clustering without expert estimations. In this paper, we presented results of experiments that confirmed better quality then traditional algorithms.

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Paper citation in several formats:
Novikov, A. and Benderskaya, E. (2014). SYNC-SOM - Double-layer Oscillatory Network for Cluster Analysis. In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-018-5; ISSN 2184-4313, SciTePress, pages 305-309. DOI: 10.5220/0004906703050309

@conference{icpram14,
author={A. V. Novikov. and E. N. Benderskaya.},
title={SYNC-SOM - Double-layer Oscillatory Network for Cluster Analysis},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2014},
pages={305-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004906703050309},
isbn={978-989-758-018-5},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - SYNC-SOM - Double-layer Oscillatory Network for Cluster Analysis
SN - 978-989-758-018-5
IS - 2184-4313
AU - Novikov, A.
AU - Benderskaya, E.
PY - 2014
SP - 305
EP - 309
DO - 10.5220/0004906703050309
PB - SciTePress