@Article{AAMM-16-3,
author = {Xianru, Chen and Lin, Li},
title = {Oversampled Collocation Approximation Method of Functions via Jacobi Frames},
journal = {Advances in Applied Mathematics and Mechanics},
year = {2024},
volume = {16},
number = {3},
pages = {569--588},
abstract = {<p style="text-align: justify;">In this paper, we study the Jacobi frame approximation with equispaced
samples and derive an error estimation. We observe numerically that the approximation accuracy gradually decreases as the extended domain parameter $\gamma$ increases in the
uniform norm, especially for differentiable functions. In addition, we show that when
the indexes of Jacobi polynomials $α$ and $β$ are larger (for example max$\{α,β\} &gt; 10$), it
leads to a divergence behavior on the frame approximation error decay.</p>},
issn = {2075-1354},
doi = {https://doi.org/10.4208/aamm.OA-2022-0071},
url = {https://global-sci.com/article/90861/oversampled-collocation-approximation-method-of-functions-via-jacobi-frames}
}