2014
DOI: 10.3934/dcdsb.2014.19.1969
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Uniform weighted estimates on pre-fractal domains

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Cited by 6 publications
(13 citation statements)
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“…As underlined before, such a trace result has potential applications to inverse problem. Similar questions at a discrete level or on higher-dimensional domains are also considered, let us quote discrete laplacian on infinite networks [11,13,15,18,[20][21][22][23], two-dimensional domains with a fractal boundary [1][2][3][4], pre-fractal domains approximating the Koch snowflake [10]. Let us finally mention some related problems such as the Hamilton-Jacobi equation [5] and the Gauss-Bonnet operator on infinite graphs [6].…”
Section: Introductionmentioning
confidence: 99%
“…As underlined before, such a trace result has potential applications to inverse problem. Similar questions at a discrete level or on higher-dimensional domains are also considered, let us quote discrete laplacian on infinite networks [11,13,15,18,[20][21][22][23], two-dimensional domains with a fractal boundary [1][2][3][4], pre-fractal domains approximating the Koch snowflake [10]. Let us finally mention some related problems such as the Hamilton-Jacobi equation [5] and the Gauss-Bonnet operator on infinite graphs [6].…”
Section: Introductionmentioning
confidence: 99%
“…Hence, Theorem 4.1 improves Theorem 3.1 also for the case α = 3. In §5, by combining the tools and methods of the paper [5] with the results of §4, we establish uniform estimates that are more accurate than those established in [5], (compare Theorems 5.1 and 3.2). Lastly, in §6 we briefly discuss how we can extend the results of previous sections to the solutions of obstacle problems.…”
mentioning
confidence: 95%
“…As the boundaries are the union of an increasing number of graphs and develop at the limit a fractal geometry, then the sharp regularity result (3.4) involves constants that might diverge as the number of graphs becomes infinite. In [5] we proved that there exists a suitable value of µ * depending on the structural parameter of the limit fractal domain 3 for which uniform weighted estimates hold. More precisely, the following result holds.…”
mentioning
confidence: 95%
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