Abstract
The block version of the rational Arnoldi method is a widely used procedure for generating an orthonormal basis of a block rational Krylov space. We study block rational Arnoldi decompositions associated with this method and prove an implicit Q theorem. We show how to choose parameters to prevent a premature breakdown of the method and improve its numerical stability by relating the decompositions to nonlinear eigenvalue problems. We explain how rational matrixvalued functions are encoded in block rational Arnoldi decompositions and how they can be evaluated numerically. Two different types of deflation strategies are discussed. Numerical illustrations using the MATLAB Rational Krylov Toolbox are included.
Original language | English |
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Journal | S I A M Journal on Matrix Analysis and Applications |
DOIs | |
Publication status | Published - 9 Apr 2020 |
Keywords
- block rational Krylov
- rational matrix-valued function
- vector autoregression