• 検索結果がありません。

(1)Akita University (2)Akita University (3)Akita University (4)Akita University (5)Akita University (6)Akita University (7)Akita University (8)Akita University (9)Akita University (10)Akita University

N/A
N/A
Protected

Academic year: 2021

シェア "(1)Akita University (2)Akita University (3)Akita University (4)Akita University (5)Akita University (6)Akita University (7)Akita University (8)Akita University (9)Akita University (10)Akita University"

Copied!
10
0
0

読み込み中.... (全文を見る)

全文

(1)

Akita University

(2)

Akita University

(3)

Akita University

(4)

Akita University

(5)

Akita University

(6)

Akita University

(7)

Akita University

(8)

Akita University

(9)

Akita University

(10)

Akita University

参照

関連したドキュメント

Note that in the nonsymmetric examples, the number of required ADI iterations j iter for the V - shifts is not always smaller than that of the heuristic shifts (see, e.g.,

These results let us hope, and later confirm, that deferred correction schemes can be established using rational interpolants with equispaced nodes, polynomial reproduction

In [32], Nobile employed the ALE formulation to first derive methods for a Newtonian fluid flow governed by the Navier-Stokes equations in a mov- ing domain, and then coupled

We have seen that under rather natural source condi- tions error estimates in Bregman distances can be extended from the well-known quadratic fitting (Gaussian noise) case to

Mainly, by using the extrapolation method, families of estimates can be derived which are valid for any nonsingular matrix and thus can be used for nonsymmetric problems. In

M AASS , A generalized conditional gradient method for nonlinear operator equations with sparsity constraints, Inverse Problems, 23 (2007), pp.. M AASS , A generalized

In summary, based on the performance of the APBBi methods and Lin’s method on the four types of randomly generated NMF problems using the aforementioned stopping criteria, we

In this paper, we extend the results of [14, 20] to general minimization-based noise level- free parameter choice rules and general spectral filter-based regularization operators..