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A note on best conditioned preconditioners

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Abstract

We discuss the solution of Hermitian positive definite systemsAx=b by the preconditioned conjugate gradient method with a preconditionerM. In general, the smaller the condition numberκ(M −1/2 AM −1/2) is, the faster the convergence rate will be. For a given unitary matrixQ, letM Q = {Q*Λ N Q | Λ n is ann-by-n complex diagonal matrix} andM + Q ={Q*Λ n Q | Λ n is ann-by-n positive definite diagonal matrix}. The preconditionerM b that minimizesκ(M −1/2 AM −1/2) overM + Q is called the best conditioned preconditioner for the matrixA overM + Q . We prove that ifQAQ* has Young's Property A, thenM b is nothing new but the minimizer of ‖MA F overM Q . Here ‖ · ‖ F denotes the Frobenius norm. Some applications are also given here.

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Jin, X.Q. A note on best conditioned preconditioners. BIT 34, 313–317 (1994). https://doi.org/10.1007/BF01955879

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  • DOI: https://doi.org/10.1007/BF01955879

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