Krylov subspace methods for estimating operator-vector multiplications in Hilbert spaces
نویسندگان
چکیده
Abstract The Krylov subspace method has been investigated and refined for approximating the behaviors of finite or infinite dimensional linear operators. It used eigenvalues, solutions equations, operator functions acting on vectors. Recently, time-series data analysis, much attention is being paid to as a viable estimating multiplications vector by an unknown referred transfer operator. In this paper, we investigate convergence analysis methods operator-vector multiplications.
منابع مشابه
Operator-valued bases on Hilbert spaces
In this paper we develop a natural generalization of Schauder basis theory, we term operator-valued basis or simply ov-basis theory, using operator-algebraic methods. We prove several results for ov-basis concerning duality, orthogonality, biorthogonality and minimality. We prove that the operators of a dual ov-basis are continuous. We also dene the concepts of Bessel, Hilbert ov-basis and obta...
متن کاملNumerical Methods for the QCD Overlap Operator: II. Optimal Krylov Subspace Methods
We investigate optimal choices for the (outer) iteration method to use when solving linear systems with Neuberger’s overlap operator in QCD. Different formulations for this operator give rise to different iterative solvers, which are optimal for the respective formulation. We compare these methods in theory and practice to find the overall optimal one. For the first time, we apply the so-called...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Japan Journal of Industrial and Applied Mathematics
سال: 2021
ISSN: ['0916-7005', '1868-937X']
DOI: https://doi.org/10.1007/s13160-021-00460-4