Spatial Weighting and Iterative Projection Methods for EOFs
نویسندگان
چکیده
منابع مشابه
Spatial Weighting and Iterative Projection Methods for EOFs
Often there is a need to consider spatial weighting in methods for finding spatial patterns in climate data. The focus of this paper is on techniques that maximize variance, such as empirical orthogonal functions (EOFs). A weighting matrix is introduced into a generalized framework for dealing with spatial weighting. One basic principal in the design of the weighting matrix is that the resultin...
متن کاملIterative Projection Methods for Structured Sparsity Regularization
In this paper we propose a general framework to characterize and solve the optimization problems underlying a large class of sparsity based regularization algorithms. More precisely, we study the minimization of learning functionals that are sums of a differentiable data term and a convex non differentiable penalty. These latter penalties have recently become popular in machine learning since t...
متن کاملOn convergence of iterative projection methods for symmetric eigenvalue problems
We prove global convergence of particular iterative projection methods using the so-called shift-and-invert technique for solving symmetric generalized eigenvalue problems. In particular, we aim to provide a variant of the convergence theorem obtained by Crouzeix, Philippe, and Sadkane for the generalized Davidson method. Our result covers the Jacobi-Davidson and the rational Krylov methods wit...
متن کاملA Class of Iterative Methods for Solving Nonlinear Projection Equations
A class of globally convergent iterative methods for solving nonlinear projection equations is provided under a continuity condition of the mapping F. When Fis pseudomonotone, a necessary and sufficient condition on the nonemptiness of the solution set is obtained.
متن کاملIterative Projection Methods for Large–scale Nonlinear Eigenvalue Problems
In this presentation we review iterative projection methods for sparse nonlinear eigenvalue problems which have proven to be very efficient. Here the eigenvalue problem is projected to a subspace V of small dimension which yields approximate eigenpairs. If an error tolerance is not met then the search space V is expanded in an iterative way with the aim that some of the eigenvalues of the reduc...
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: Journal of Climate
سال: 2009
ISSN: 1520-0442,0894-8755
DOI: 10.1175/2008jcli2147.1