Compressed Sensing lets us capture signal data – in a digital photo or MRI scan, for example – from very few measurements. Developed by mathematicians in the early 2000s, compressed sensing now powers your mobile phone camera, MRI scanners, electron microscopes, and radio telescopes. The key idea is that real-world signals are highly structured (sparse) and this lets us reconstruct signals by solving a much easier problem: finding the shortest vector in a “space of signals”.
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