Showing papers by "Zhong-Zhi Bai published in 2021"

TL;DR: An exact closed-form formula is conducted for the mean-squared residual of the iterate generated by the randomized Gauss-Seidel method, and an upper bound for the convergence rate of the randomizedGauss- Seidel method is estimated.

TL;DR: Both theoretical analysis and numerical experiments show that the preconditioned Krylov subspace iteration methods can exhibit optimal convergence property in the sense that their convergence rates are independent of both discretization stepsizes and problem parameters, and their computational workloads are linearly proportional with the number of discrete unknowns.

TL;DR: Both theoretical analysis and numerical experiments show that the parameterized power methods can result in iteration methods that may be much more effective than the power method, provided the involved iteration parameters are chosen appropriately.

TL;DR: In this paper, the generalized Bendixson theorem with respect to a square complex matrix pair has been extended to square complex matrices, and simplified versions of it have been provided.