Adaptive solution of partial di erential equations in multiwavelet bases

By B. Alpert, Gregory Beylkin, D. Gines, L. Vozovoi. 2002

278 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computational Theory and Mathematics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/03ee1099dbc3f9c4dce29608c3c555ca1428837e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Mehdi Dehghan

In Computational Theory and Mathematics

1. Mehdi Dehghan
2. Feng Ding
3. Masoud Hajarian
4. Ali Shokri

In Computer Vision and Pattern Recognition

1. S. Irandoust‐pakchin
2. Mehdi Dehghan
3. Mehrdad Lakestani

Citations in the corpus

• Numerical solution for a class of fractional convection–diffusion equations using the flatlet oblique multiwavelets (2014, background): “It should be noted that despite the fact that smoothness is a suitable feature for problems such as signal processing and image decomposition, thus far, non-smooth wavelets have provided desirable results in certain numerical methods (Alpert et al., 2002; Dahmen et al., 2000).”
• Multiwavelet-based Operator Learning for Differential Equations (2021, background): “A uniform measure (μ0) version is discussed in [4], and we extend it to any arbitrary measure by including the correction terms Σ and Σ((1)).”