Long-range prediction for real-time MPEG video traffic: An H ∞ filter approach

Chih Hu Wang; Bor Sen Chen; Bore Kuen Lee; Tsu Tian Lee; Chien-Nan Liu; Chau-Chin Su

doi:10.1109/TCSVT.2008.2004926

Long-range prediction for real-time MPEG video traffic: An H ∞ filter approach

Chih Hu Wang^*, Bor Sen Chen, Bore Kuen Lee, Tsu Tian Lee, Chien-Nan Liu, Chau-Chin Su

^*此作品的通信作者

研究成果: Article › 同行評審

4 引文斯高帕斯（Scopus）

摘要

A novel prediction scheme is proposed for real-time MPEG video to predict the burst and long-range dependent traffic. The trend and periodic characteristics of MPEG video traffic are fully captured by a proposed stochastic state-space dynamic model. Then a recursive H_∞ filtering algorithm is proposed to estimate traffic for long-range prediction. Simulation results based on real MPEG traffic data show that the proposed scheme has superior performance and lower complexity than some adaptive neural network methods, such as TDNN, NARX, and Elman neural networks.

原文	English
文章編號	4625974
頁（從 - 到）	1771-1775
頁數	5
期刊	IEEE Transactions on Circuits and Systems for Video Technology
卷	18
發行號	12
DOIs	https://doi.org/10.1109/TCSVT.2008.2004926
出版狀態	Published - 1 12月 2008

存取文件

10.1109/TCSVT.2008.2004926

其它文件與鏈接

Link to publication in Scopus

引用此

@article{cf30769c09904ca29a2d21d74228ccf0,

title = "Long-range prediction for real-time MPEG video traffic: An H ∞ filter approach",

abstract = "A novel prediction scheme is proposed for real-time MPEG video to predict the burst and long-range dependent traffic. The trend and periodic characteristics of MPEG video traffic are fully captured by a proposed stochastic state-space dynamic model. Then a recursive H∞ filtering algorithm is proposed to estimate traffic for long-range prediction. Simulation results based on real MPEG traffic data show that the proposed scheme has superior performance and lower complexity than some adaptive neural network methods, such as TDNN, NARX, and Elman neural networks.",

keywords = "H filter, Long-range dependence, MPEG video, State-space method",

author = "Wang, {Chih Hu} and Chen, {Bor Sen} and Lee, {Bore Kuen} and Lee, {Tsu Tian} and Chien-Nan Liu and Chau-Chin Su",

year = "2008",

month = dec,

day = "1",

doi = "10.1109/TCSVT.2008.2004926",

language = "English",

volume = "18",

pages = "1771--1775",

journal = "IEEE Transactions on Circuits and Systems for Video Technology",

issn = "1051-8215",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "12",

}

TY - JOUR

T1 - Long-range prediction for real-time MPEG video traffic

T2 - An H ∞ filter approach

AU - Wang, Chih Hu

AU - Chen, Bor Sen

AU - Lee, Bore Kuen

AU - Lee, Tsu Tian

AU - Liu, Chien-Nan

AU - Su, Chau-Chin

PY - 2008/12/1

Y1 - 2008/12/1

N2 - A novel prediction scheme is proposed for real-time MPEG video to predict the burst and long-range dependent traffic. The trend and periodic characteristics of MPEG video traffic are fully captured by a proposed stochastic state-space dynamic model. Then a recursive H∞ filtering algorithm is proposed to estimate traffic for long-range prediction. Simulation results based on real MPEG traffic data show that the proposed scheme has superior performance and lower complexity than some adaptive neural network methods, such as TDNN, NARX, and Elman neural networks.

AB - A novel prediction scheme is proposed for real-time MPEG video to predict the burst and long-range dependent traffic. The trend and periodic characteristics of MPEG video traffic are fully captured by a proposed stochastic state-space dynamic model. Then a recursive H∞ filtering algorithm is proposed to estimate traffic for long-range prediction. Simulation results based on real MPEG traffic data show that the proposed scheme has superior performance and lower complexity than some adaptive neural network methods, such as TDNN, NARX, and Elman neural networks.

KW - H filter

KW - Long-range dependence

KW - MPEG video

KW - State-space method

UR - http://www.scopus.com/inward/record.url?scp=56849109260&partnerID=8YFLogxK

U2 - 10.1109/TCSVT.2008.2004926

DO - 10.1109/TCSVT.2008.2004926

M3 - Article

AN - SCOPUS:56849109260

SN - 1051-8215

VL - 18

SP - 1771

EP - 1775

JO - IEEE Transactions on Circuits and Systems for Video Technology

JF - IEEE Transactions on Circuits and Systems for Video Technology

IS - 12

M1 - 4625974

ER -

Long-range prediction for real-time MPEG video traffic: An H ∞ filter approach

摘要

存取文件

其它文件與鏈接

指紋

引用此