Invited by School of Mathematics and Statistics, Prof. Ning Bi from Sun Yat-Sen University willgive a lecture.

Title: The NSP for sparse vector recovery via minimization

Time: 10:30 a.m.,May.22nd, 2021

Location: Room 506 ,the College Student Activity Center

Abstract: In this talk, we focus on minimization model, i.e., investigating the nonconvex model，and provide a null space property of the measurement matrix such that a vector can be recovered from via minimization. The minimization model was first proposed by E. Esser, et al. [A Method for Finding Structured Sparse Solution to Nonnegative Least Squares Problems with Applications, SIAM J. Imag. Sci., 6(4) (2013), 2010–2046]. As a nonconvex model, it is well known that global minimizer and local minimizer are usually inconsistent. In this talk, we present a necessary and sufficient condition for the measurement matrix such that (1) a vector can be recovered from via local minimization; (2) any k-sparse vector can be recovered from via local minimization; (3) any k-sparse vector can be recovered from via .