4 ms·

Here is a good lecture on this subject: https://www.youtube.com/watch?v=rt5mMEmZHfs https://www.youtube.com/watch?v=rt5mMEmZHfs

• geokon 10mo ago
  That was actually fantastic. The professor is quite goofy, but he really goes over everything from first principles and goes through a real example - constructing a solution without any cheating :)) I was a bit bummed out there weren't a lot of Compressed Sensing libraries around, but it seems you just need a "convex optimization" routine (aka linear programming). And these seem to exist in every language I'll try to play around with this! Thank you so much
  • NL807 10mo ago
    It's a fascinating topic and i'm still trying to get my head around some of the concepts. Have fun on your discovery journey.
    • geokon 10mo ago
      Are there any gotchas you've come across? From the video tutorial is seems relatively straightforward. I guess the basis selection is a fundamental issue that will be problem-specific. I will have to try it with some concrete examples. The first question I have is, will it still work if you have a lot of high frequency noise? In the cases I'm thinking either there is measurement noise or just other jitter. So while the lower frequencies are sparse but I guess the higher frequencies not so much. I can't bandpass the data b/c it's got lots of holes or it's irregularly spaced. Maybe it'll still work though!