In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is symmetric and positive definite. The conjugate gradient method is an iterative method, so it can be applied to sparse systems which are too large to be handled by direct methods such as the Cholesky decomposition. Such systems arise regularly when numerically solving partial differential equations.
T. Trosterud, and K. Unhammer. Proceedings of the Third International Workshop on Free/Open-Source Rule-Based Machine Translation (FreeRBMT 2012), 2013:03, page 13--26. Gothenburg, Sweden, Chalmers University of Technology, (June 2012)