Existence minimizer for total variation over measures

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I want to prove that there exists a minimizer to the following problem $$ \min || \mu ||_{\text{TV}} \text{ such that } \mathcal{F} \mu = y $$

where $\mu \in \mathcal{M}([0,1])$, the space of Radon measures in the interval $[0,1]$, and $\mathcal{F}: \mathcal{M}([0,1]) \to \mathbb{C}^n$ is some linear operator, to which we know that $\mathcal{F}^{-1} y \neq \{ \emptyset \}$.

Typically for convex problems like this, I would approach it by using convexity and lower semi-continuity of the total variation norm. But since the underlying space is (I think) not reflexive, there is no weak compacity for closed, convex, bounded sets.

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Typically, you can use that $\mathcal M(([0,1])$ is the dual space of the separable space $C([0,1])$. Hence, for every bounded sequence you can extract weak-$*$ convergent subsequences. If $\mathcal F$ is also continuous w.r.t. the weak-$*$ convergent sequences, then you can do the usual arguments. If you do not know this (additional) continuity of $\mathcal F$, the existence of minimizers may fail.