Extraction of topological features from communication network topological patterns using self-organizing feature maps
Neural and Evolutionary Computing
2007-05-23 v2 Computer Vision and Pattern Recognition
Abstract
Different classes of communication network topologies and their representation in the form of adjacency matrix and its eigenvalues are presented. A self-organizing feature map neural network is used to map different classes of communication network topological patterns. The neural network simulation results are reported.
Cite
@article{arxiv.cs/0404042,
title = {Extraction of topological features from communication network topological patterns using self-organizing feature maps},
author = {W. Ali and R. J. Mondragon and F. Alavi},
journal= {arXiv preprint arXiv:cs/0404042},
year = {2007}
}
Comments
8 Pages, 5 figures, To be appeared in IEE Electronics Letter Journal