نتایج جستجو برای: krylov subspace methods

تعداد نتایج: 1887528  

Journal: :The Journal of chemical physics 2012
Tadashi Ando Edmond Chow Yousef Saad Jeffrey Skolnick

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a brownian dynamics simulation. However, the calculation of correlated brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studie...

2012
Tadashi Ando Edmond Chow Yousef Saad Jeffrey Skolnick

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a Brownian dynamics simulation. However, the calculation of correlated Brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studie...

Journal: :SIAM Journal on Matrix Analysis and Applications 2011

2017
ERIN C. CARSON

Algebraic solvers based on preconditioned Krylov subspace methods are among the most powerful tools for large scale numerical computations in applied mathematics, sciences, technology, as well as in emerging applications in social sciences. As the name suggests, Krylov subspace methods can be viewed as a sequence of projections onto nested subspaces of increasing dimension. They are therefore b...

2011
Yin Zhang

Stationary iterative methods for solving systems of linear equations are considered by some as out of date and out of favor, as compared to methods based on Krylov subspace iterations. However, these methods are still useful in many circumstances because they are easier to implement and, more importantly, can be used as pre-conditioners in combination with Krylov-subspace methods. In this note,...

2012
Per Christian Hansen

Image deblurring, i.e., reconstruction of a sharper image from a blurred and noisy one, involves the solution of a large and very ill-conditioned system of linear equations, and regularization is needed in order to compute a stable solution. Krylov subspace methods are often ideally suited for this task: their iterative nature is a natural way to handle such largescale problems, and the underly...

Journal: :SIAM Journal on Matrix Analysis and Applications 2010

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