  Let $(\{f_j\}_{j=1}^n, \{\tau_j\}_{j=1}^n)$ and $(\{g_k\}_{k=1}^m,
\{\omega_k\}_{k=1}^m)$ 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 \|\theta_f x\|_0^\frac{1}{p}\|\theta_g
x\|_0^\frac{1}{q} \geq \frac{1}{\displaystyle\max_{1\leq j\leq n, 1\leq k\leq
m}|f_j(\omega_k)|}\quad \text{and} \quad \|\theta_g x\|_0^\frac{1}{p}\|\theta_f
x\|_0^\frac{1}{q}\geq \frac{1}{\displaystyle\max_{1\leq j\leq n, 1\leq k\leq
m}|g_k(\tau_j)|}. \end{align} where \begin{align*} \theta_f: \mathcal{X} \ni x
\mapsto (f_j(x) )_{j=1}^n \in \ell^p([n]); \quad \theta_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-Torr\'{e}sani Uncertainty Principle}.
Inequality (1) improves Ricaud-Torr\'{e}sani 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]}.
