Shortest path routing algorithm using Hopfield neural network

C. W. Ahn, R. S. Ramakrishna, Chung Gu Kang, In Chan Choi

Research output: Contribution to journalArticle

59 Citations (Scopus)

Abstract

A near-optimal routing algorithm employing a modified Hopfield neural network (HNN) is presented. Since it uses every piece of information that is available at the peripheral neurons, in addition to the highly correlated information that is available at the local neuron, faster convergence and better route optimality is achieved than with existing algorithms that employ the HNN. Furthermore, all the results are relatively independent of network topology for almost all source-destination pairs.

Original languageEnglish
Pages (from-to)1176-1178
Number of pages3
JournalElectronics Letters
Volume37
Issue number19
DOIs
Publication statusPublished - 2001 Sep 13

Fingerprint

Hopfield neural networks
Routing algorithms
Neurons
Topology

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Shortest path routing algorithm using Hopfield neural network. / Ahn, C. W.; Ramakrishna, R. S.; Kang, Chung Gu; Choi, In Chan.

In: Electronics Letters, Vol. 37, No. 19, 13.09.2001, p. 1176-1178.

Research output: Contribution to journalArticle

Ahn, C. W. ; Ramakrishna, R. S. ; Kang, Chung Gu ; Choi, In Chan. / Shortest path routing algorithm using Hopfield neural network. In: Electronics Letters. 2001 ; Vol. 37, No. 19. pp. 1176-1178.
@article{a5eb3ab4e43a4822904b90dc938c235b,
title = "Shortest path routing algorithm using Hopfield neural network",
abstract = "A near-optimal routing algorithm employing a modified Hopfield neural network (HNN) is presented. Since it uses every piece of information that is available at the peripheral neurons, in addition to the highly correlated information that is available at the local neuron, faster convergence and better route optimality is achieved than with existing algorithms that employ the HNN. Furthermore, all the results are relatively independent of network topology for almost all source-destination pairs.",
author = "Ahn, {C. W.} and Ramakrishna, {R. S.} and Kang, {Chung Gu} and Choi, {In Chan}",
year = "2001",
month = "9",
day = "13",
doi = "10.1049/el:20010800",
language = "English",
volume = "37",
pages = "1176--1178",
journal = "Electronics Letters",
issn = "0013-5194",
publisher = "Institution of Engineering and Technology",
number = "19",

}

TY - JOUR

T1 - Shortest path routing algorithm using Hopfield neural network

AU - Ahn, C. W.

AU - Ramakrishna, R. S.

AU - Kang, Chung Gu

AU - Choi, In Chan

PY - 2001/9/13

Y1 - 2001/9/13

N2 - A near-optimal routing algorithm employing a modified Hopfield neural network (HNN) is presented. Since it uses every piece of information that is available at the peripheral neurons, in addition to the highly correlated information that is available at the local neuron, faster convergence and better route optimality is achieved than with existing algorithms that employ the HNN. Furthermore, all the results are relatively independent of network topology for almost all source-destination pairs.

AB - A near-optimal routing algorithm employing a modified Hopfield neural network (HNN) is presented. Since it uses every piece of information that is available at the peripheral neurons, in addition to the highly correlated information that is available at the local neuron, faster convergence and better route optimality is achieved than with existing algorithms that employ the HNN. Furthermore, all the results are relatively independent of network topology for almost all source-destination pairs.

UR - http://www.scopus.com/inward/record.url?scp=0035855703&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0035855703&partnerID=8YFLogxK

U2 - 10.1049/el:20010800

DO - 10.1049/el:20010800

M3 - Article

AN - SCOPUS:0035855703

VL - 37

SP - 1176

EP - 1178

JO - Electronics Letters

JF - Electronics Letters

SN - 0013-5194

IS - 19

ER -