Dror Baron - Compressed Sensing Hardware

Compressed sensing (CS) is a new framework for integrated sensing and compression. The fundamental revelation is that, if an N-sample signal x is sparse and has a good K-term approximation in some basis, then it can be reconstructed using M =O(K log(N/K)) << N linear projections of x onto another basis. Furthermore, x can be reconstructed using linear programming, which has polynomial complexity. Some of the CS projects I have worked on are described here, and links to numerous other papers appear on the Nuit Blanche blog and the compressed sensing resource page.

This webpage describes hardware-related CS projects that I have been involved in.

Compressed sensing camera: We developed a single-pixel CS camera that takes a random projection of an image with a pattern of zeros and ones by bouncing light off an array of micro-mirrors and collecting photons at a single photodiode.
Compressive Imaging

New analog-to-digital converters: Current analog to digital converters are too slow to sample wideband signals at their Nyquist frequency. However, for sparse signals the Nyquist frequency is a worst-case bound on the requisite measurement rate. Our techniques project the signal directly in analog hardware by modulating and then filtering an analog signal, and then digitize at a reduced sampling rate.
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Last updated June 2014.