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The Nonlocal p-Laplacian Evolution Problem on Graphs: The Continuum Limit

机译:图中的非局部p-laplacian进化问题:连续箱限制

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The non-local p-Laplacian evolution equation, governed by given kernel, has various applications to model diffusion phenomena, in particular in signal and image processing. In practice, such an evolution equation is implemented in discrete form (in space and time) as a numerical approximation to a continuous problem, where the kernel is replaced by an adjacency matrix of graph. The natural question that arises is to understand the structure of solutions to the discrete problem, and study their continuous limit. This is the goal pursued in this work. Combining tools from graph theory and non-linear evolution equations, we give a rigorous interpretation to the continuous limit of the discrete p-Laplacian on graphs. More specifically, we consider a sequence of deterministic simple/weighted graphs converging to a so-called graphon. The continuous p-Laplacian evolution equation is then discretized on this graph sequence both in space and time. We therefore prove that the solutions of the sequence of discrete problems converge to the solution of the continuous evolution problem governed by the graphon, when the number of graph vertices grows to infinity. We exhibit the corresponding convergence rates for different graph models, and point out the role of the graphon geometry and the parameter p.
机译:由给定内核管辖的非局部P-LAPLACIAN演化方程具有模拟扩散现象的各种应用,特别是在信号和图像处理中。在实践中,这种演化方程以离散形式(空间和时间)实现为连续问题的数值近似,其中内核由图形的邻接矩阵替换。出现的自然问题是了解对离散问题的解决方案的结构,并研究其连续限制。这是在这项工作中追求的目标。与图论和非线性演化方程组合的工具,我们对图形上的离散P-LAPLACIAN的连续极限进行了严格的解释。更具体地,我们考虑一系列确定的简单/加权图汇聚到所谓的Graphon。然后在空间和时间内将连续的P-LAPLACIAN演化方程分离在该图序列上。因此,当图形顶点的数量生长到无穷大时,我们证明了离散问题序列的解决方案会聚到图形管理的连续演化问题的解决方案。我们展示了不同图形模型的相应收敛速率,并指出了石墨几何和参数P的作用。

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