The need to evaluate expressions of the form f (A)v, where A is a large sparse or structured symmetric matrix, v is a vector, and f is a nonlinear function, arises in many applications. The extended Krylov subspace method can be an attractive scheme for computing approximations of such expressions.
Krylov type subspace methods for matrix polynomials
β Scribed by Leonard Hoffnung; Ren-Cang Li; Qiang Ye
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 329 KB
- Volume
- 415
- Category
- Article
- ISSN
- 0024-3795
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