Differentiability of the distance function and points of multi-valuedness of the metric projection in Banach space
Dini-Campanato spaces and applications to nonlinear elliptic equations.
Direct and Converse Theorems for Generalized Bernstein-Type Operators
2000 Mathematics Subject Classification: 41A25, 41A27, 41A36.We establish direct and converse theorems for generalized parameter dependent Bernstein-type operators. The direct estimate is given using a K-functional and the inverse result is a strong converse inequality of type A, in the terminology of [2].
Direct and inverse theorems for Szâsz-lupas type operators in simultaneous approximation
Direct approximation theorems for discrete type operators.
Direct results for certain family of integral type operators.
Direct results for mixed Beta-Szász type operators.
Directions d'uniforme convexité dans un espace normé
Discrete approximation of the solution of the Dirichlet problem by discrete means.
Discrete Approximations to Spherically Symmetric Distributions.
Discrete Cubic Spline Interpolation
Discrete, Linear Approximation Problems in Polyhedral Norms.
Discrete linear interpolatory operators.
Discrete L-Splines.
Discrete, Nonlinear Approximation Problems in Polyhedral Norms.
Discrete, Nonlinear Approximation Problems in Polyhedral Norms. A Levenberg-Like Algorithm.
Discrete quadratic splines.
Discrete smoothing splines and digital filtration. Theory and applications
Two universally applicable smoothing operations adjustable to meet the specific properties of the given smoothing problem are widely used: 1. Smoothing splines and 2. Smoothing digital convolution filters. The first operation is related to the data vector with respect to the operations , and to the smoothing parameter . The resulting function is denoted by . The measured sample is defined on an equally spaced mesh
Dispersed Chebyshev Sets and Coverings by Balls.
Distinguishing and integrating aleatoric and epistemic variation in uncertainty quantification
Much of uncertainty quantification to date has focused on determining the effect of variables modeled probabilistically, and with a known distribution, on some physical or engineering system. We develop methods to obtain information on the system when the distributions of some variables are known exactly, others are known only approximately, and perhaps others are not modeled as random variables at all.The main tool used is the duality between risk-sensitive integrals and relative entropy, and we...