Highly Influenced

# Error Bounds for the Krylov Subspace Methods for Computations of Matrix Exponentials

@article{Wang2017ErrorBF, title={Error Bounds for the Krylov Subspace Methods for Computations of Matrix Exponentials}, author={Hao Wang and Qiang Ye}, journal={SIAM J. Matrix Analysis Applications}, year={2017}, volume={38}, pages={155-187} }

- Published 2017 in SIAM J. Matrix Analysis Applications
DOI:10.1137/16M1063733

In this paper, we present new a posteriori and a priori error bounds for the Krylov subspace methods for computing e−τAv for a given τ > 0 and v ∈ Cn, where A is a large sparse nonHermitian matrix. The a priori error bounds relate the convergence to λmin( A+A∗ 2 ), λmax( A+A∗ 2 ) (the smallest and the largest eigenvalue of the Hermitian part of A), and |λmax(A−A 2 )| (the largest eigenvalue in absolute value of the skew-Hermitian part of A), which define a rectangular region enclosing the field… CONTINUE READING