论文标题
部分可观测时空混沌系统的无模型预测
Lattice and Non-lattice Piercing of Axis-Parallel Rectangles: Exact Algorithms and a Separation Result
论文作者
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。
For a given family of shapes ${\mathcal F}$ in the plane, we study what is the lowest possible density of a point set $P$ that pierces ("intersects", "hits") all translates of each shape in ${\mathcal F}$. For instance, if ${\mathcal F}$ consists of two axis-parallel rectangles the best known piercing set, i.e., one with the lowest density, is a lattice: for certain families the known lattices are provably optimal whereas for other, those lattices are just the best piercing sets currently known. Given a finite family ${\mathcal F}$ of axis-parallel rectangles, we present two algorithms for finding an optimal ${\mathcal F}$-piercing lattice. Both algorithms run in time polynomial in the number of rectangles and the maximum aspect ratio of the rectangles in the family. No prior algorithms were known for this problem. Then we prove that for every $n \geq 3$, there exist a family of $n$ axis-parallel rectangles for which the best piercing density achieved by a lattice is separated by a positive (constant) gap from the optimal piercing density for the respective family. Finally, we sharpen our separation result by running the first algorithm on a suitable instance, and show that the best lattice can be sometimes worse by $20\%$ than the optimal piercing set.