Compressed Sensing has seen continuous research for the past 10 years, including the famous demonstration at Rice University in 2006 when researchers produced images with resolution of tens of thousands of pixels using a camera whose sensor had just one pixel. The purpose of the technique is to extract extra information from a signal which it does not seem to contain.

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Compressed Sensing promises reduced cost and power consumption over a range of signal processing applications on paper, yet hasn't been considered practically feasible. Hoping to turn that around, MIT Researchers are working on compressed-sensing design that delivers in real-world. Recent applications of Compressed Sensing, for example spectrum sensing, where wireless devices scan the airwaves and detect unused frequencies for use have promised significant power savings but only achieved a fraction. Still, Researchers continue to explore alternate ways to solution including the application of sparse Fast Fourier Transform to avoid loss of resolution and increase power savings in spectrum-sensing.

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