The General Neville-Aitken-Algorithm and Some Applications.
The General Recurrence Relation for Divided Differences and the General Newton-Interpolation-Algorithm With Applications to Trigonometric Interpolation.
The generalizations of Newton's interpolation formula due to Mühlbach and Andoyer.
The interplay between classical analysis and (numerical) linear algebra -- a tribute to Gene H. Golub.
The inverse of the star-discrepancy depends linearly on the dimension
The Nash-Kuiper process for curves
A strictly short embedding is an embedding of a Riemannian manifold into an Euclidean space that strictly shortens distances. From such an embedding, the Nash-Kuiper process builds a sequence of maps converging toward an isometric embedding. In that paper, we describe this Nash-Kuiper process in the case of curves. We state an explicit formula for the limit normal map and perform its Fourier series expansion. We then adress the question of Holder regularity of the limit map.
The numerical computation of a class of divergent integrals
The Numerical Computation of the Confluent Hypergeometric Function U(a,b,z)
The Numerical Evaluation of Cauchy Principal Values of Integrals by Romberg-Integration.
The Numerical Evaluation of Hadamard Finite-part Integrals.
The Numerical Evaluation of Principal Value Integrals by Finite-Part Integration.
The Optimal Recovery of Smooth Function.
The polar form of a polynomial surface.
The properties, inequalities and numerical approximation of modified Bessel functions.
The QD-Algorithm and Multivariate Padé-Approximants.
The quantized Jacobi polynomials
The author studies a system of polynomials orthogonal at a finite set of points its weight approximating that of the orthogonal system of classical Jacobi polynomials.
The Remainder Term in Quadrature Formulae.
The Use of Splines and Singular Functions in an Integral Equation Method for Conformai Mapping.
The Weierstrass Mean. I. The periods of ...(z|e1, e2, e3).
Theoretical analysis for - minimization with partial support information
We investigate the recovery of -sparse signals using the - minimization model with prior support set information. The prior support set information, which is believed to contain the indices of nonzero signal elements, significantly enhances the performance of compressive recovery by improving accuracy, efficiency, reducing complexity, expanding applicability, and enhancing robustness. We assume -sparse signals with the prior support which is composed of true indices and wrong indices,...