CS: The Compressed-Sampling Filter (CSF)

I've mentioned it before but it looks like an improved version of The Design of Compressive Sensing Filter by Lianlin Li, Wenji Zhang, Yin Xiang, Fang Li. The newer publication presents two compressive sensing hardware implementation in The Compressed-Sampling Filter (CSF) by Lianlin Li, Wenji Zhang, Yin Xiang, Fang Li.. The abstract reads:

The common approaches to sample a signal generally follow the well-known Nyquist-Shannon's theorem: the sampling rate must be at least twice the maximum frequency presented in the signal. A new emerging field, compressed sampling (CS), has made a paradigmatic step to sample a signal with much less measurements than those required by the Nyquist-Shannon's theorem when the unknown signal is sparse or compressible in some frame. We call a compressed-sampling filter (CSF) one for which the function relating the input signal to the output signal is pseudo-random. Motivated by the theory of random convolution proposed by Romberg (for convenience, called the Romberg's theory) and the fact that the signal in complex electromagnetic environment may be spread out due to the rich multi-scattering effect, two CSFs via microwave circuit to enable signal acquisition with sub-Nyquist sampling have been constructed, tested and analyzed. Afterwards, the CSF based on surface acoustic wave (SAW) structure has also been proposed and examined by the numerical simulation. The results has empirically shown that by the proposed architectures the S-sparse n-dimensional signal can be exactly reconstructed with O(Slogn) real-valued measurements or O(Slog(n/S)) complex-valued measurements with overwhelming probability.

As one can read in the paper, the detailed parameters about this CSF for reproducing the results in this paper can be downloaded from to-cs.blog.sohu.com or can also be obtained by e-mail: lianlinli1980@gmail.com. This information can also be downloaded from here. Thanks Lianlin ! I note the following nuggets:

...Maybe, some defective product of SAW time delayer may be an excellent candidate for the purpose of compressed sampling measurement....

I've had similar thoughts about diverse systems and think it may be a good path toward starting disruptive technologies using unused assets or assets that people want to discard. Also in a different direction, we have:

...Of course, the general compressive sensing filter can be constructed along the identical idea by many other structures, the plasma with different electron density corresponding to different critical frequency. As a matter of fact, the ionosphere can be looked as the natural compressive sensing measurement system...

Emphasis is mine, this is the paper that made me think of the Imaging With Nature series of blog entries. The series won't stop at three entries and I am sure we won't stop hearing about it from Lianlin either (translation is here). Both hardware will be added to the Compressive Sensing Hardware page.