Announcement of Lecture Course
Spring Semester 2013 / 2014
Compressed sensing and random matrices
Compressed sensing is an active research topic recently. The main goal of compressed sensing is to recover the sparse signal from a few measurements. We will give an introduction about the basic results in compressed sensing and also show many interesting research problems. In particular, we introduce the relation between random matrixes and compressed sensing.
The investigation of the spectral properties of matrices, whose entries are random variables, is the goal of random matrix theory. We will learn different probabilistic techniques for the study of random matrixes.
R. Vershynin. Introduction to the non-asymptotic analysis of random matrices. http://arxiv.org/abs/1011.3027.
E. J. Candes, J. Romberg, and T. Tao, Stable signal recovery from incomplete and inaccurate measurements, Comm. Pure Appl. Math., 59(8)(2006)1207-1223.
许志强，Compressed sensing, A survey in Chinese, Sci Sin Math, 2012, 42(9)。
Time: March.7- June 13, Friday, 13:30, N308.