TY - JOUR
T1 - A discrete-time recurrent neural network for shortest-path routing
AU - Xia, Youshen
AU - Wang, Jun
PY - 2000
Y1 - 2000
N2 - This paper 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 characteristicsof the proposed neural network are demonstrated by means of simulation results. © 2000 IEEE.
AB - This paper 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 characteristicsof the proposed neural network are demonstrated by means of simulation results. © 2000 IEEE.
KW - Combinatorial optimization
KW - Discrete-time
KW - Neural networks
KW - Shortest-path routing
UR - http://www.scopus.com/inward/record.url?scp=0034316660&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0034316660&origin=recordpage
U2 - 10.1109/9.887639
DO - 10.1109/9.887639
M3 - RGC 21 - Publication in refereed journal
SN - 0018-9286
VL - 45
SP - 2129
EP - 2134
JO - IEEE Transactions on Automatic Control
JF - IEEE Transactions on Automatic Control
IS - 11
ER -