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CORR
2008
Springer

Gaussian Belief Propagation for Solving Systems of Linear Equations: Theory and Application

8 years 10 months ago
Gaussian Belief Propagation for Solving Systems of Linear Equations: Theory and Application
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 address the properties of the GaBP solver, including convergence, exactness, computational complexity, message-passing efficiency and its relation to classical solution methods. We use numerical examples and applications, like linear detection, to illustrate these properties through the use of computer simulations. This empirical study demonstrates the attractiveness (e.g. , faster convergence rate) of the proposed GaBP solver in comparison to conventional linear-algebraic iterative solution methods.
Ori Shental, Danny Bickson, Paul H. Siegel, Jack K
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where CORR
Authors Ori Shental, Danny Bickson, Paul H. Siegel, Jack K. Wolf, Danny Dolev
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