论文标题

部分可观测时空混沌系统的无模型预测

Row-column factorial designs with strength at least $2$

论文作者

Rahim, Fahim, Cavenagh, Nicholas J.

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。

The $q^k$ (full) factorial design with replication $λ$ is the multi-set consisting of $λ$ occurrences of each element of each $q$-ary vector of length $k$; we denote this by $λ\times [q]^k$. An $m\times n$ row-column factorial design $q^k$ of strength $t$ is an arrangement of the elements of $λ\times [q]^k$ into an $m\times n$ array (which we say is of type $I_k(m,n,q,t)$) such that for each row (column), the set of vectors therein are the rows of an orthogonal array of degree $k$, size $n$ (respectively, $m$), $q$ levels and strength $t$. Such arrays are used in experimental design. In this context, for a row-column factorial design of strength $t$, all subsets of interactions of size at most $t$ can be estimated without confounding by the row and column blocking factors. In this manuscript, we study row-column factorial designs with strength $t\geq 2$. Our results for strength $t=2$ are as follows. For any prime power $q$ and assuming $2\leq M\leq N$, we show that there exists an array of type $I_k(q^M,q^N,q,2)$ if and only if $k\leq M+N$, $k\leq (q^M-1)/(q-1)$ and $(k,M,q)\neq (3,2,2)$. We find necessary and sufficient conditions for the existence of $I_{k}(4m,n,2,2)$ for small parameters. We also show that $I_{k+α}(2^αb,2^k,2,2)$ exists whenever $α\geq 2$ and $2^α+α+1\leq k<2^αb-α$, assuming there exists a Hadamard matrix of order $4b$. For $t=3$ we focus on the binary case. Assuming $M\leq N$, there exists an array of type $I_k(2^M,2^N,2,3)$ if and only if $M\geq 5$, $k\leq M+N$ and $k\leq 2^{M-1}$. Most of our constructions use linear algebra, often in application to existing orthogonal arrays and Hadamard matrices.

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