DocumentCode :
2519144
Title :
Gaussian belief propagation solver for systems of linear equations
Author :
Shental, Ori ; Siegel, Paul H. ; Wolf, Jack K. ; Bickson, Danny ; Dolev, Danny
Author_Institution :
Center for Magn. Recording Res., Univ. of California - San Diego, La Jolla, CA
fYear :
2008
fDate :
6-11 July 2008
Firstpage :
1863
Lastpage :
1867
Abstract :
The canonical problem of solving a system of linear equations arises in numerous contexts in information theory, communication theory, and related fields. In this contribution, we develop a solution based upon Gaussian belief propagation (GaBP) that does not involve direct matrix inversion. The iterative nature of our approach allows for a distributed message-passing implementation of the solution algorithm. We also address some properties of the GaBP solver, including convergence, exactness, its max-product version and relation to classical solution methods. The application example of decorrelation in CDMA is used to demonstrate the faster convergence rate of the proposed solver in comparison to conventional linear-algebraic iterative solution methods.
Keywords :
Bayes methods; Gaussian processes; code division multiple access; decorrelation; iterative methods; message passing; CDMA; Gaussian belief propagation solver; canonical problem; convergence rate; decorrelation; distributed message-passing implementation; iterative method; linear equations; Belief propagation; Equations; Graphical models; Iterative algorithms; Iterative methods; Lifting equipment; Linear systems; Sparse matrices; Symmetric matrices; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory, 2008. ISIT 2008. IEEE International Symposium on
Conference_Location :
Toronto, ON
Print_ISBN :
978-1-4244-2256-2
Electronic_ISBN :
978-1-4244-2257-9
Type :
conf
DOI :
10.1109/ISIT.2008.4595311
Filename :
4595311
Link To Document :
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