Compressed Sensing / Sampling

I’m still trying to push ID forward as science. I previously suggest Bendford’s Law might be a fruitful avenue for ID research, but there were no takers I know of. Recently I came across Compressed Sensing, and I think this might also be a concept IDist want to explore. Here is the Wikipedia page:

http://en.wikipedia.org/wiki/Compressed_sensing

See also:

http://authors.library.caltech.edu/10092/1/CANieeespm08.pdf

It seems to be able to recreate structured datasets with surprisingly high fidelity from very low samples. Could it be used to find a hallmark of design?
So, Barry@UD – time to stop the apologetics wagon and do some science. Unfortunately you’ve banned the brightest minds at UD but a couple of the regulars might want to have a crack at this?

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