论文标题
部分可观测时空混沌系统的无模型预测
The average density of K-normal elements over finite fields
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。
Let $q$ be a prime power and, for each positive integer $n\ge 1$, let $\mathbb F_{q^n}$ be the finite field with $q^n$ elements. Motivated by the well known concept of normal elements over finite fields, Huczynska et al (2013) introduced the notion of $k$-normal elements. More precisely, for a given $0\le k\le n$, an element $α\in \mathbb F_{q^n}$ is $k$-normal over $\mathbb F_q$ if the $\mathbb F_q$-vector space generated by the elements in the set $\{α, α^q, \ldots, α^{q^{n-1}}\}$ has dimension $n-k$. The case $k=0$ recovers the normal elements. If $q$ and $k$ are fixed, one may consider the number $λ_{q, n, k}$ of elements $α\in \mathbb F_{q^n}$ that are $k$-normal over $\mathbb F_q$ and the density $λ_{q, k}(n)=\frac{λ_{q, n, k}}{q^n}$ of such elements in $\mathbb F_{q^n}$. In this paper we prove that the arithmetic function $λ_{q, k}(n)$ has positive mean value, in the sense that the limit $$\lim\limits_{t\to +\infty}\frac{1}{t}\sum_{1\le n\le t}λ_{q, k}(n),$$ exists and it is positive.