$(X, ||• ||) $ be a $d$ dimensional normed linear space over $K$.
$\beta = \{e_1,e_2,e_3,...,e_d\} \text {be a basis of } X $.
Given any, $x\in X$ has a unique representation of the form
$x= x_1 e_1 + x_2 e_2 +... +x_n e_n (x_j \in K,\forall j\in \mathbb{N}_d ) $
Then, $(x_1, x_2, x_3,..., x_d) $ is defined to be the coordinate of $x$ with respect to $\beta$.
Question : $$\text{ Given any sequence} (x^{(n)}) _{n\in \mathbb{N}}\text{ and } x \text{ in } X $$
$(x^{(n)})$$ \text{ converges to } x \text { iff it converges Co-ordinatewise. }$
My attempt :
$(x^{(n)}) _{n\in \mathbb{N}} \text{ is sequence in } X $
$\text{ where the n-th term }$
$x^{(n)}=(x_{1}^{(n)},x_{2}^{(n)},..., x_{d}^{(n)}) $
And, $x= (x_1, x_2,..., x_d) $
And, $(x_{j}^{(n)})$ converges to $x_j$
$|x_{j}^{(n)} - x_j | < \frac{\epsilon}{\sum_{n=1}^{d}{||e_{j}||}} $ $(\forall n\ge N_{j} \text { and } j \in \mathbb {N}_d) $
To show, $(x^{(n) })_{n \in \mathbb{N}}$ converges to $x$ in $(X, ||•||) $ \begin{align} ||x^{(n) }- x || &=||\sum_{n=1}^{d}{(x_{j}^{(n)} - x_j) e_j ||} \\ &\le \sum_{n=1}^{d}{|(x_{j}^{(n)} - x_j)| \text{ } {|| e_j||}}\\ &< \epsilon \text { }(\forall n \ge max{\mathbb\{N_j\}} \end{align}
Hence, $(x^{(n) })_{n \in \mathbb{N}}$ converges to $x$ in $(X, ||•||) $
Is my proof of first part is correct?
How can I prove the reverse implication?
Thanks.