1000th member of the compressive sensing study group on LinkedIn would be. Well, we now have an answer. What is most important however is that I noticed that discussions on the group have been of higher quality lately. The group is not open, you have to be part of it to participate in the discussions but here are some interesting discussions that went on recently:
- Please suggest algorithms for cluster-structured sparse signals
- Are there 3rd-party databases for evaluating the performance of reconstruction algorithms?
- Optimization with multiple non-standard regularizers
- Noise Distribution after CS-reconstruction?
Thanks to Thomas Arildsen, R. H. Sri Hari, Ravi Kiran B., and Alejandro Weinstein for helping out in managing the group.
Obviously, the blog provides a way to enable that precious discussion off-line as well as noted by Hyrum Anderson about this entry on Greg Charvat's class I featured and announced earlier:
I'm the nuit-blanche reader that Greg Charvat referenced...and whose coffee-can SAR image of Kresge Auditorium you posted today on your blog.
A plug for Greg and his course: I would encourage your readers (radar folks or not) to look into any future course offerings that Greg teaches. The class is quite intense, but Greg has contagious enthusiasm...so despite the diverse skillset of students, everyone was able to make their own coffee-can radar capable of SAR imaging.
My next step is to put together some algorithms and collect my own sparse dataset to "build your own compressive sensing coffee-can SAR".
Thanks for the blog!
For those of you interested, besides starting a discussion in the comment section of this blog, I am also on Twitter and Google +. If you are having a hangout of sorts related to CS, let me know.
Credit: NASA, Chicago from the international space station, photo taken by Ron Garan.