Compressed Sensing and Sigma-Delta Quantization
|Speaker:||Dr. Feng, Joe-Mei|
|Date:||2018-09-13 (Thu) 10:30 - 12:00|
|Location:||Auditorium 122 at CITI|
This talk concerns about the recovery error of a quantized compressed sensing problem. More specifically, Sigma-Delta quantization will be used through out this talk, and restricted isometry property (RIP) is used as the criterion on compressed sensing matrices. The situations on using sub-gaussian partial random circulant matrices as compressed sensing matrices will be discussed. Results on partial random Fourier matrices will be given.