论文标题

部分可观测时空混沌系统的无模型预测

Separating bichromatic point sets in the plane by restricted orientation convex hulls

论文作者

Alegría, Carlos, Orden, David, Seara, Carlos, Urrutia, Jorge

论文摘要

储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。

We explore the separability of point sets in the plane by a restricted-orientation convex hull, which is an orientation-dependent, possibly disconnected, and non-convex enclosing shape that generalizes the convex hull. Let $R$ and $B$ be two disjoint sets of red and blue points in the plane, and $\mathcal{O}$ be a set of $k \geq 2$ lines passing through the origin. We study the problem of computing the set of orientations of the lines of $\mathcal{O}$ for which the $\mathcal{O}$-convex hull of $R$ contains no points of $B$. For $k=2$ orthogonal lines we have the rectilinear convex hull. In optimal $O(n \log n)$ time and $O(n)$ space, $n = \vert R \vert + \vert B \vert$, we compute the set of rotation angles such that, after simultaneously rotating the lines of $\mathcal{O}$ around the origin in the same direction, the rectilinear convex hull of $R$ contains no points of $B$. We generalize this result to the case where $\mathcal{O}$ is formed by $k \geq 2$ lines with arbitrary orientations. In the counter-clockwise circular order of the lines of $\mathcal{O}$, let $α_i$ be the angle required to clockwise rotate the $i$th line so it coincides with its successor. We solve the problem in this case in $O(1/Θ\cdot N \log N)$ time and $O(1/Θ\cdot N)$ space, where $Θ= \min \{ α_1,\ldots,α_k \}$ and $N=\max\{k,\vert R \vert + \vert B \vert \}$. We finally consider the case in which $\mathcal{O}$ is formed by $k=2$ lines, one of the lines is fixed, and the second line rotates by an angle that goes from $0$ to $π$. We show that this last case can also be solved in optimal $O(n\log n)$ time and $O(n)$ space, where $n = \vert R \vert + \vert B \vert$.

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