Actively-induced percolation: An effective approach to multiple-object systems characterization
Disordered Systems and Neural Networks
2007-05-23 v2
Abstract
The present work proposes the concept of induced percolation over multiple-object systems, so that features such as the number of merged clusters can be used as a relevant measurement. The suggested approach involves the expansion of the objects while monitoring the evolving clusters. The potential of the proposed methodology for characterizing the spatial interaction and distribution between several objects is illustrated with respect to synthetic and real data.
Cite
@article{arxiv.cond-mat/0404310,
title = {Actively-induced percolation: An effective approach to multiple-object systems characterization},
author = {Luciano da Fontoura Costa},
journal= {arXiv preprint arXiv:cond-mat/0404310},
year = {2007}
}
Comments
5 pages, 4 figures