DocumentCode :
1411594
Title :
A discrete-time recurrent neural network for shortest-path routing
Author :
Xia, Youshen ; Wang, Jun
Author_Institution :
Dept. of Autom. & Comput.-Aided Eng., Chinese Univ. of Hong Kong, Shatin, China
Volume :
45
Issue :
11
fYear :
2000
fDate :
11/1/2000 12:00:00 AM
Firstpage :
2129
Lastpage :
2134
Abstract :
Presents a discrete-time recurrent neural network, with a fixed step parameter, for solving the shortest path problem. The proposed discrete-time recurrent neural network with a simple architecture is proven to be globally convergent to exact optimal solutions and is suitable for hardware implementation. Furthermore, an improved network with a larger step size independent of the problem size is proposed to increase its convergence rate. The performance and operating characteristics of the proposed neural network are demonstrated by means of simulation results.
Keywords :
directed graphs; discrete time systems; minimisation; recurrent neural nets; convergence rate; discrete-time recurrent neural network; exact optimal solutions; global convergence; operating characteristics; performance characteristics; shortest-path routing; Approximation algorithms; Artificial neural networks; Computer networks; Costs; Neural networks; Path planning; Recurrent neural networks; Routing; Shortest path problem; Telecommunication traffic;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/9.887639
Filename :
887639
Link To Document :
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