Local approximation using hermite functions

6Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We develop a wavelet-like representation of functions in Lp.(R) based on their Fourier-Hermite coefficients; i.e., we describe an expansion of such functions where the local behavior of the terms characterize completely the local smoothness of the target function. In the case of continuous functions, a similar expansion is given based on the values of the functions at arbitrary points on the real line. In the process, we give new proofs for the localization of certain kernels, as well as for some very classical estimates such as the Markov-Bernstein inequality.

Cite

CITATION STYLE

APA

Mhaskar, H. N. (2017). Local approximation using hermite functions. In Springer Optimization and Its Applications (Vol. 117, pp. 341–362). Springer International Publishing. https://doi.org/10.1007/978-3-319-49242-1_16

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free