Comments on why generalized BP serves so remarkably in 2-D channels

Ori Shental; Noam Shental; Shlomo Shamai; Ido Kanter; Anthony J. Weiss; Yair Weiss

doi:10.1109/ITA.2007.4357604

Comments on why generalized BP serves so remarkably in 2-D channels

Ori Shental^*, Noam Shental, Shlomo Shamai, Ido Kanter, Anthony J. Weiss, Yair Weiss

^*Corresponding author for this work

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Generalized belief propagation (GBP) algorithm has been shown recently to infer the a-posteriori probabilities of finite-state input two-dimensional (2-D) Gaussian channels with memory in a practically accurate manner, thus enabling near-optimal estimation of the transmitted symbols and the Shannon-theoretic information rates. In this note, a rationalization of this excellent performance of GBP is addressed.

Original language	English
Title of host publication	2007 Information Theory and Applications Workshop, Conference Proceedings, ITA
Pages	369
Number of pages	1
DOIs	https://doi.org/10.1109/ITA.2007.4357604
State	Published - 2007
Event	2007 Information Theory and Applications Workshop, ITA - San Diego, CA, United States Duration: 29 Jan 2007 → 2 Feb 2007

Publication series

Name	2007 Information Theory and Applications Workshop, Conference Proceedings, ITA

Conference

Conference	2007 Information Theory and Applications Workshop, ITA
Country/Territory	United States
City	San Diego, CA
Period	29/01/07 → 2/02/07

Access to Document

10.1109/ITA.2007.4357604

Cite this

Shental, O., Shental, N., Shamai, S., Kanter, I., Weiss, A. J., & Weiss, Y. (2007). Comments on why generalized BP serves so remarkably in 2-D channels. In 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA (pp. 369). [4357604] (2007 Information Theory and Applications Workshop, Conference Proceedings, ITA). https://doi.org/10.1109/ITA.2007.4357604

@inproceedings{862a792cef2441d2a05c955165f25379,

title = "Comments on why generalized BP serves so remarkably in 2-D channels",

abstract = "Generalized belief propagation (GBP) algorithm has been shown recently to infer the a-posteriori probabilities of finite-state input two-dimensional (2-D) Gaussian channels with memory in a practically accurate manner, thus enabling near-optimal estimation of the transmitted symbols and the Shannon-theoretic information rates. In this note, a rationalization of this excellent performance of GBP is addressed.",

author = "Ori Shental and Noam Shental and Shlomo Shamai and Ido Kanter and Weiss, {Anthony J.} and Yair Weiss",

year = "2007",

doi = "10.1109/ITA.2007.4357604",

language = "אנגלית",

isbn = "9780615153148",

series = "2007 Information Theory and Applications Workshop, Conference Proceedings, ITA",

pages = "369",

booktitle = "2007 Information Theory and Applications Workshop, Conference Proceedings, ITA",

note = "null ; Conference date: 29-01-2007 Through 02-02-2007",

}

Shental, O, Shental, N, Shamai, S, Kanter, I, Weiss, AJ & Weiss, Y 2007, Comments on why generalized BP serves so remarkably in 2-D channels. in 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA., 4357604, 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA, pp. 369, 2007 Information Theory and Applications Workshop, ITA, San Diego, CA, United States, 29/01/07. https://doi.org/10.1109/ITA.2007.4357604

Comments on why generalized BP serves so remarkably in 2-D channels. / Shental, Ori; Shental, Noam; Shamai, Shlomo et al.

2007 Information Theory and Applications Workshop, Conference Proceedings, ITA. 2007. p. 369 4357604 (2007 Information Theory and Applications Workshop, Conference Proceedings, ITA).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Comments on why generalized BP serves so remarkably in 2-D channels

AU - Shental, Ori

AU - Shental, Noam

AU - Shamai, Shlomo

AU - Kanter, Ido

AU - Weiss, Anthony J.

AU - Weiss, Yair

PY - 2007

Y1 - 2007

N2 - Generalized belief propagation (GBP) algorithm has been shown recently to infer the a-posteriori probabilities of finite-state input two-dimensional (2-D) Gaussian channels with memory in a practically accurate manner, thus enabling near-optimal estimation of the transmitted symbols and the Shannon-theoretic information rates. In this note, a rationalization of this excellent performance of GBP is addressed.

AB - Generalized belief propagation (GBP) algorithm has been shown recently to infer the a-posteriori probabilities of finite-state input two-dimensional (2-D) Gaussian channels with memory in a practically accurate manner, thus enabling near-optimal estimation of the transmitted symbols and the Shannon-theoretic information rates. In this note, a rationalization of this excellent performance of GBP is addressed.

UR - http://www.scopus.com/inward/record.url?scp=48049099625&partnerID=8YFLogxK

U2 - 10.1109/ITA.2007.4357604

DO - 10.1109/ITA.2007.4357604

M3 - פרסום בספר כנס

AN - SCOPUS:48049099625

SN - 9780615153148

T3 - 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA

SP - 369

BT - 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA

Y2 - 29 January 2007 through 2 February 2007

ER -

Comments on why generalized BP serves so remarkably in 2-D channels

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this