Arnoldi

基本解释

For nonlinear model order reductions, three new algorithms based on quadratic method and Arnoldi process are proposed.
对于非线性系统的模型降阶算法，本文将提出一类新的基于Taylor展开的二次化方法与Arnoldi过程相结合的算法。
For linear model reduction algorithms, The Krylov subspace based algorithms including Arnoldi process and Lanczos algorithm are introduced.
同时对于这两种常见的模型降阶算法，本文将给出相关的误差分析。
In order to improve the quality of the Ritz vectors, in Chapter 4 a strategy proposed by Jia and Elsner is generalized to the block Arnoldi version.
为了改进Ritz向量的性能，在第四章中我们将Jia和Elsner的一种策略推广到块Arnoldi情形。
The efficiency of the Jacobi-Davidson method at initial iteration steps is improved by using the Arnoldi decomposition to construct the initial orthogonal subspace.
针对Jacobi-Davidson方法在迭代初期效率低下的问题，提出了用Arnoldi分解构造正交子空间作为初始子空间的方案，有效地改善了迭代初期的计算效率。
As to the Power Ground RLC equivalent circuit with a large number of independent current sources, we propose a novel HOAR (High Order ARnoldi) based MOR method.
在电源地网络RLC等效电路降阶分析方面，我们提出了一种新的基于高次Arnoldi过程的降阶算法HOAR。