An_improved_neural_network_model_for_the_2-page_crossing_number_problem.pdf (285.43 kB)
Download file

An improved neural network model for the two-page crossing number problem

Download (285.43 kB)
journal contribution
posted on 25.09.2006, 13:39 authored by Hongmei He, Ondrej Sykora, Erkki Makinen
The simplest graph drawing method is that of putting the vertices of a graph on a line and drawing the edges as half-circles either above or below the line. Such drawings are called 2-page book drawings. The smallest number of crossings over all 2-page drawings of a graph G is called the 2-page crossing number of G. Cimikowski and Shope have solved the 2-page crossing number problem for an n-vertex and m-edge graph by using a Hopfield network with 2m neurons. We present here an improved Hopfield modelwith m neurons. The new model achieves much better performance in the quality of solutions and is more efficient than the model of Cimikowski and Shope for all graphs tested. The parallel time complexity of the algorithm, without considering the crossing number calculations, is O(m), for the new Hopfield model with m processors clearly outperforming the previous algorithm.

History

School

  • Science

Department

  • Computer Science

Pages

196069 bytes

Citation

HE, H., SÝKORA, O. and MÄKINEN, E., 2006. An improved neural network model for the two-page crossing number problem. IEEE Transactions on Neural Neworks, 17 (6), pp.1642-1646

Publisher

© IEEE Computational Intelligence Society

Publication date

2006

Notes

This article was published in the journal, IEEE Transactions on Neural Networks [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN

1045-9227

Language

en