Neural network approach for communication network routing problem

Author

Liu Rong ; Liu Ze-Min ; Zhou Zheng

Author_Institution

Beijing Univ. of Posts & Telecommun., China

Volume

3

fYear

1993

fDate

19-21 Oct. 1993

Firstpage

649

Abstract

A description of the Hopfield/Tank model used for the communication network routing problem is given. Then, through "static" (i.e. the eigenvalue and the eigenspace of the connection matrix) and the dynamic analyses of the model, it is found that the model has the fastest rate to converge to the optimal or near-optimal solutions from an initial value. Therefore the quality of the final solutions can be guaranteed. The influence of the initial value on the final solutions is also considered. Simulation results are given at the end of the paper.<>

Keywords

Hopfield neural nets; convergence of numerical methods; eigenvalues and eigenfunctions; matrix algebra; telecommunication network routing; Hopfield/Tank model; communication network routing problem; convergence rate; dynamic analyses; initial value; near-optimal solutions; neural network approach; optimal solutions; static analyses; Communication networks; Costs; Eigenvalues and eigenfunctions; Hopfield neural networks; Large-scale systems; Military communication; Neural networks; Neurons; Routing; Telecommunication traffic;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on

Conference_Location

Beijing, China

Print_ISBN

0-7803-1233-3

Type

conf

DOI

10.1109/TENCON.1993.328071

Filename

328071