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 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
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
T2 - 2007 Information Theory and Applications Workshop, ITA
Y2 - 29 January 2007 through 2 February 2007
ER -