New answers tagged compressive-sensing
1
You can employ Compressed Sensing / Sparse Representation for Super Resolution in Frequency Domain.
One way to do so is solving the problem:
$$ \arg \min_{\boldsymbol{x}} \frac{1}{2} {\left\| F \boldsymbol{x} - \boldsymbol{y} \right\|}_{2}^{2} + \lambda {\left\| \boldsymbol{x} \right\|}_{1} $$
Where the $ {L}_{1} $ norm is sparsity inducing regularization ...
2
This question is typically the subject of a paper like Robust Uncertainty Principles: Exact Signal Reconstruction From Highly Incomplete Frequency Information, Emmanuel J. Candès, Justin Romberg, 2006:
This paper considers the model problem of reconstructing an object
from incomplete frequency samples. Consider a discrete-time signal
$f\in \mathbb{C}^N$ and ...
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compressive-sensing × 121optimization × 22
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