VC dimension bound of a union of mapping hypothesis sets

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Consider the following feature transform, which maps a d-dimensional $x$ to a one-dimension $z$, keeping only the $k$th coordinate of $x$

$\phi_{(k)}(x)=(1,x_k)$

Let $H_k$ be the set of perceptrons in the feature space.

Prove that $d_{vc}(\cup_{k=1}^dH_k) \leq 2(\log_2d+1)$.

I have no idea about this question, for I do not know how to introduce the $\log_2$ int my inequality.