M-MUX / FM-MUX : Compressive Multiplexers for Correlated Signals

Here is an interesting architecture for sensing signals sharing much in common

Compressive Multiplexers for Correlated Signals by Ali Ahmed and Justin Romberg. The abstract reads:

We propose two compressive multiplexers for the efficient sampling of ensembles of correlated signals. We show that we can acquire correlated ensembles, taking advantage of their (a priori-unknown) correlation structure, at a sub-Nyquist rate using simple modulation and filtering architectures. We recast the reconstruction of the ensemble as a low-rank matrix recovery problem from generalized linear measurements. Our theoretical results indicate that we can recover an ensemble of M correlated signals composed of R M independent signals, each bandlimited to W=2 Hz, by taking O(RW logq W) samples per second, where q > 1 is a small constant.

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