Supplemental Materials for “ Spectral Compressed Sensing via Structured Matrix Completion ”
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چکیده
This supplemental document presents details concerning analytical derivations that support the theorems made in the main text " Spectral Compressed Sensing via Structured Matrix Completion " , accepted to the 30th International Conference on Machine Learning (ICML 2013). One can find here the detailed proof of Theorems 1-3.
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Spectral Compressed Sensing via Structured Matrix Completion
The paper studies the problem of recovering a spectrally sparse object from a small number of time domain samples. Specifically, the object of interest with ambient dimension n is assumed to be a mixture of r complex multi-dimensional sinusoids, while the underlying frequencies can assume any value in the unit disk. Conventional compressed sensing paradigms suffer from the basis mismatch issue ...
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