English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we study the Jacobi frame approximation with equispacedsamples and derive an error estimation. We observe numerically that theapproximation accuracy gradually decreases as the extended domain parameter$\gamma$ increases in the uniform norm, especially for differentiablefunctions. In addition, we show that when the indexes of Jacobi polynomials$\alpha$ and $\beta$ are larger (for example $\max\{\alpha,\beta\} > 10$), itleads to a divergence behavior on the frame approximation error decay.

Stable approximation of functions from equispaced samples via Jacobi frames