J. T. Parker, V. Cevher, and P. Schniter, ``Compressive Sensing under Multiplicative Uncertainties: An Approximate Message Passing Approach,'' submitted to Proc. Asilomar Conf. on Signals, Systems, and Computers (Pacific Grove, CA), Nov. 2011
on Phil Schniter's page.From the Call of Paper of the conference:
Notifications of acceptance will be mailed by mid July 2011, and author information will be available on the conference website by late July 2011.
I and the hardware folks, look forward to the results of this investigation! Thanks Jason, Phil, Volkan for looking into this important problem. It is important the way Hamming describes it in his speech You and Your Research:
...Over on the other side of the dining hall was a chemistry table. I had worked with one of the fellows, Dave McCall; furthermore he was courting our secretary at the time. I went over and said, ``Do you mind if I join you?'' They can't say no, so I started eating with them for a while. And I started asking, ``What are the important problems of your field?'' And after a week or so, ``What important problems are you working on?'' And after some more time I came in one day and said, ``If what you are doing is not important, and if you don't think it is going to lead to something important, why are you at Bell Labs working on it?'' I wasn't welcomed after that; I had to find somebody else to eat with! That was in the spring....
Currently the important problems in our field is the mismatch between the promises of compressive sensing and its current hardware implementation. An important sub-problem is figuring out the level of "noise" admissible so that we can fulfill the promises of these random sensing systems. In this instance, this is the job of the applied math folks to provide the hardware sensing crowd with actual requirements, even if that means that the sensor has to be much better.