Large-dimension image clustering by means of fragmentary synchronization in chaotic systems

Benderskaya, Elena N.; Zhukova, Sofya V.

doi:10.1134/s1054661809020151

Cited by 5 publications

(1 citation statement)

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“…The oscillatory networks provide biologically plausible and parallel methods of modeling cognitive functions. The synchronization processes in oscillatory networks have been applied to various problems such as image segmentation, cluster analysis, sound and image recognition (Basar, 1998); (Cumin et al, 2006); (Benderskaya et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

SYNC-SOM - Double-layer Oscillatory Network for Cluster Analysis

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Benderskaya

2014

Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods

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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. Novikov A. and Benderskaya E.. SYNC-SOM-Double-layer Oscillatory Network for Cluster Analysis.

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Section: Introductionmentioning

confidence: 99%