A Characterization of C(X) Among Algebras on Planar Sets by the Existence of a Finite Universal Korovkin System.
A characterization of random approximations.
A characterization of strictly convex metric linear spaces.
A class of generalized best approximation problems in locally convex linear topological spaces.
A classification of projectors
A positive operator A and a closed subspace of a Hilbert space ℋ are called compatible if there exists a projector Q onto such that AQ = Q*A. Compatibility is shown to depend on the existence of certain decompositions of ℋ and the ranges of A and . It also depends on a certain angle between A() and the orthogonal of .
A Computational Procedure for the Approximation of Random Functions.
A Continuous Selection of the Metric Projection in Matrix Spaces, Addendum.
A density theorem for locally convex lattices.
A discrete integral representation for polynomials of fixed maximal degree and their universal Korovkin closure.
A generalization of an Ekeland-Lebourg theorem and the differentiability of distance functions
A method of approximation of spaces of generalized functions
A non-Chebyshev finite-dimensional subspace in
A note on a two-weighted Sobolev inequality
A note on Chebyshev centres
A note on f-best approximation in reflexive Banach spaces
A note on Kakutani type fixed point theorems.
A note on rotation in separable Banach spaces
A Note on Suns in Convex Metric Spaces
A priori convergence of the greedy algorithm for the parametrized reduced basis method
The convergence and efficiency of the reduced basis method used for the approximation of the solutions to a class of problems written as a parametrized PDE depends heavily on the choice of the elements that constitute the “reduced basis”. The purpose of this paper is to analyze the a priori convergence for one of the approaches used for the selection of these elements, the greedy algorithm. Under natural hypothesis on the set of all solutions to the problem obtained when the parameter varies, we...
A priori convergence of the Greedy algorithm for the parametrized reduced basis method
The convergence and efficiency of the reduced basis method used for the approximation of the solutions to a class of problems written as a parametrized PDE depends heavily on the choice of the elements that constitute the “reduced basis”. The purpose of this paper is to analyze the a priori convergence for one of the approaches used for the selection of these elements, the greedy algorithm. Under natural hypothesis on the set of all solutions to the problem obtained when the parameter varies, we...