Discrete-time recurrent neural network for shortest-path routing

Jun Wang, Youshen Xia

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

This paper presents a discrete-time recurrent neural network for solving the shortest path problem. The proposed discrete-time recurrent neural network is proven to be globally convergent to an exact solution. In addition, the proposed neural network has fixed design parameters and simple architecture, thus is more suitable for hardware implementation. Furthermore, an improved network with a larger step size is proposed to increase the convergence rate. The performance and operating characteristics of the proposed neural network are demonstrated by means of simulation results.

Original languageEnglish
Pages (from-to)1579-1584
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
Publication statusPublished - 1998
Externally publishedYes
EventProceedings of the 1998 37th IEEE Conference on Decision and Control (CDC) - Tampa, FL, USA
Duration: 16 Dec 199818 Dec 1998

Fingerprint

Dive into the research topics of 'Discrete-time recurrent neural network for shortest-path routing'. Together they form a unique fingerprint.

Cite this