Solving the delay constrained multicast routing problem using the transiently chaotic neural network

Wen Liu*, Lipo Wang

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

2 Citations (Scopus)

Abstract

Delay constrained multicast routing (DCMR) aims to construct a minimum-cost tree with end-to-end delay constraints. This routing problem is becoming more and more important to multimedia applications which are delay-sensitive and require real time communications. We solve the DCMR problem by the transiently chaotic neural network (TCNN) of Chen and Aihara. Simulation results show that the TCNN is more capable of reaching global optima compared with the Hopfield neural network (HNN).

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
PublisherSpringer Verlag
Pages57-62
Number of pages6
EditionPART 2
ISBN (Print)9783540723929
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China
Duration: 3 Jun 20077 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume4492 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Symposium on Neural Networks, ISNN 2007
Country/TerritoryChina
CityNanjing
Period3/06/077/06/07

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