The content discusses the comparison between Galerkin, Pseudo-Minimal Residual (PMR), and Minimal Residual (MR) methods for solving large-scale Lyapunov matrix equations. The author proposes a new approach that modifies the Galerkin method to achieve better convergence rates similar to MR schemes while maintaining lower computational costs. Various numerical examples are presented to demonstrate the effectiveness of this new approach.
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