Let $V$ be a vector space of a finite dimension.
Let $ B = \left \{v_1,....v_n \right \} \subseteq V$, such that $\text{dim}(\text{Span}(B)) = k$
Let $C = (\lambda_1,....\lambda_n ) \subseteq V^{*}$ be a sequence of arbitrary linear functionals.
We'll define the following $n \times n$ matrix by: $$ A = \begin{pmatrix} \lambda_1(v_1) & \cdots & \lambda_1(v_n)\\ \vdots & & \vdots\\ \lambda_n(v_1)& \cdots & \lambda_n(v_n) \end{pmatrix}$$
Prove that $rank(A) \leq k $
I can understand why $rank(A) \leq k $, but I really trouble myself finding the correct way to put it down. i'd love to get some help in this manner!
We can solve it via a well-known conclusion $$ \text{rank} (AB) \le \min \{\text{rank} (A), \text{rank} (B)\}$$
In order to reveal this, we just need to transform the original problem as follows
Considering that $\dim \text{Span} (B) =k$, we write $$ \tilde{v}_i = (v_{i1},v_{i2},\cdots,v_{ik}) \quad\forall \, 1\le i \le n $$ Then the elements in the dual space can be regarded as dual vectors $$ \tilde{\lambda}_i = (\lambda_{i1},\lambda_{i2},\cdots,\lambda_{ik}) \quad\forall \, 1\le i \le n $$ and we have $$\lambda_i(v_j) = \tilde{\lambda}_i \cdot \tilde{v}_j$$
Thus $$ A= \begin{pmatrix} \tilde{\lambda}_1 \\ \vdots \\ \tilde{\lambda}_n \end{pmatrix} \left( \tilde{v}_1^T,\cdots, \tilde{v}_n^T \right) $$ Then the conclusion mentioned above yields that $\text{rank}(A) \le \text{rank} \left( \tilde{v}_1^T,\cdots, \tilde{v}_n^T \right)= k$