Let $(\{f_j\}_{j=1}^n, \{τ_j\}_{j=1}^n)$ and $(\{g_k\}_{k=1}^m, \{ω_k\}_{k=1}^m)$ be p-Schauder frames for a finite dimensional Banach space $\mathcal{X}$. Then for every $x \in \mathcal{X}\setminus\{0\}$, we show that \begin{align} (1) \quad \|θ_f x\|_0^\frac{1}{p}\|θ_g x\|_0^\frac{1}{q} \geq \frac{1}{\displaystyle\max_{1\leq j\leq n, 1\leq k\leq m}|f_j(ω_k)|}\quad \text{and} \quad \|θ_g x\|_0^\frac{1}{p}\|θ_f x\|_0^\frac{1}{q}\geq \frac{1}{\displaystyle\max_{1\leq j\leq n, 1\leq k\leq m}|g_k(τ_j)|}. \end{align} where \begin{align*} θ_f: \mathcal{X} \ni x \mapsto (f_j(x) )_{j=1}^n \in \ell^p([n]); \quad θ_g: \mathcal{X} \ni x \mapsto (g_k(x) )_{k=1}^m \in \ell^p([m]) \end{align*} and $q$ is the conjugate index of $p$. We call Inequality (1) as \textbf{Functional Donoho-Stark-Elad-Bruckstein-Ricaud-Torrésani Uncertainty Principle}. Inequality (1) improves Ricaud-Torrésani uncertainty principle \textit{[IEEE Trans. Inform. Theory, 2013]}. In particular, it improves Elad-Bruckstein uncertainty principle \textit{[IEEE Trans. Inform. Theory, 2002]} and Donoho-Stark uncertainty principle \textit{[SIAM J. Appl. Math., 1989]}.
翻译:设 $(\{f_j\}_{j=1}^n, \{τ_j\}_{j=1}^n)$ 和 $(\{g_k\}_{k=1}^m, \{ω_k\}_{k=1}^m)$ 是有限维 Banach 空间 $\mathcal{X}$ 上的 p-Schauder 框架。则对每个 $x \in \mathcal{X}\setminus\{0\}$,我们证明
\begin{align}
(1) \quad \|θ_f x\|_0^\frac{1}{p}\|θ_g x\|_0^\frac{1}{q} \geq \frac{1}{\displaystyle\max_{1\leq j\leq n, 1\leq k\leq m}|f_j(ω_k)|}\quad \text{且} \quad \|θ_g x\|_0^\frac{1}{p}\|θ_f x\|_0^\frac{1}{q}\geq \frac{1}{\displaystyle\max_{1\leq j\leq n, 1\leq k\leq m}|g_k(τ_j)|}.
\end{align}
其中
\begin{align*}
θ_f: \mathcal{X} \ni x \mapsto (f_j(x) )_{j=1}^n \in \ell^p([n]); \quad θ_g: \mathcal{X} \ni x \mapsto (g_k(x) )_{k=1}^m \in \ell^p([m])
\end{align*}
且 $q$ 是 $p$ 的共轭指标。我们将不等式 (1) 称为 \textbf{Functional Donoho-Stark-Elad-Bruckstein-Ricaud-Torrésani 不确定性原理}。不等式 (1) 改进了 Ricaud-Torrésani 不确定性原理 \textit{[IEEE Trans. Inform. Theory, 2013]}。特别地,它改进了 Elad-Bruckstein 不确定性原理 \textit{[IEEE Trans. Inform. Theory, 2002]} 和 Donoho-Stark 不确定性原理 \textit{[SIAM J. Appl. Math., 1989]}。