Ben Krasnow On Compressive Sensing of Back-scattered X-Rays

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See the video description for some links: 

Here's the python example that was the inspiration for this: https://web.archive.org/web/20180630083729/http://www.pyrunner.com/weblog/2016/05/26/compressed-sensing-python/ and here's Steve Brunton's Compressed Sensing playlist:

There is a book to go with this series: Data Driven Science & Engineering by Steven Brunton & Nathan Kutz.

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Here's Nathan Kutz giving an example in Matlab. Here's the web page for his book Data Driven Modeling & Scientific Computation: https://faculty.washington.edu/kutz/KutzBook/KutzBook.html

Ben actually explains it better than Nathan Katz does. As well the broad-band assumption in the Nyquist-Shannon Sampling Theorem there is another assumption which is that the samples are taken at regular intervals and this is what allows high-frequency aliasing. Otherwise the sample frequency is clumped and this has an anti-aliasing effect.

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For some applications, see Angela Collier Building A Radio Telescope in Her Back Yard and This is Really Interesting - Detecting Moving Objects Using Multiple Cameras and also Matt Godbolt Explaining the Difference Between a US$150 Microphone and The Kind you Get Built-in to a Laptop.