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Defined dimensions of vectors, ranked parameters of problem.
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It is known that given corrupt measurements $y = Af+e$$y = Af+e \in \mathbb{R}^m$ with $f \in \mathbb{R}^n$ and $\|f\|_0 < m < n$, one can recover an input vector $f \in \textbf{R}^n$$f$ exactly by solving a convex optimization problem. What if $f$ is instead a square matrix? Can we recover a matrix from corrupt measurements instead of just a vector?

It is known that given corrupt measurements $y = Af+e$ one can recover an input vector $f \in \textbf{R}^n$ exactly by solving a convex optimization problem. What if $f$ is instead a square matrix? Can we recover a matrix from corrupt measurements instead of just a vector?

It is known that given corrupt measurements $y = Af+e \in \mathbb{R}^m$ with $f \in \mathbb{R}^n$ and $\|f\|_0 < m < n$, one can recover $f$ exactly by solving a convex optimization problem. What if $f$ is instead a square matrix? Can we recover a matrix from corrupt measurements instead of just a vector?

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Recovering a matrix instead of a vector

It is known that given corrupt measurements $y = Af+e$ one can recover an input vector $f \in \textbf{R}^n$ exactly by solving a convex optimization problem. What if $f$ is instead a square matrix? Can we recover a matrix from corrupt measurements instead of just a vector?