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We present a novel algorithm, named the 2D-FFAST, to compute a sparse 2D-Discrete Fourier Transform (2D-DFT) featuring both low sample complexity and low computational complexity.
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S. Pawar and K. Ramchandran, “Computing a k-sparse n-length discrete fourier transform using at most 4k samples and o (k log k) complexity,” in Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on . IEEE, 2013, pp. 464–468. [Online]. Available: \url
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S. Pawar and K. Ramchandran, “A robust R-FFAST framework for computing a k-sparse n-length DFT in O (k log n) sample complexity using sparse-graph codes,” Information Theory (ISIT) , pp. 1852–1856, 2014. [Online]. Available: \url
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