Tata Institute of Fundamental Research
Sparse Solutions to Under-determined Systems of Linear Equations
Student Seminar
Speaker:
Kishore Barman
Tata Institute of Fundamental Research
School of Technology and Computer Science
Homi Bhabha Road
Date:
Friday, 30 Apr 2010 (all day)
Venue:
A-212 (STCS Seminar Room)
(Scan to add to calendar)
Abstract:
An under-determined system of linear equation has infinitely many solutions (if it has a solution). But, if we have some prior knowledge saying that the solution vector is sparse enough, then under certain conditions there exists a unique solution. Moreover we can find the solution in polynomial time by solving a linear program. This is a celebrated result (by Candes and Tao) that has created a whole new area called *Compressed sensing* . In this talk I will introduce the problem, and will prove a simple version of such reconstruction of sparse vectors from an under-determined system of linear equations.
(For everything that you want to know about compressed sensing, visit http://dsp.rice.edu/cs)
| Speaker: | Kishore Barman Tata Institute of Fundamental Research School of Technology and Computer Science Homi Bhabha Road |
| Date: | Friday, 30 Apr 2010 (all day) |
| Venue: | A-212 (STCS Seminar Room) |
(Scan to add to calendar)
Abstract:
An under-determined system of linear equation has infinitely many solutions (if it has a solution). But, if we have some prior knowledge saying that the solution vector is sparse enough, then under certain conditions there exists a unique solution. Moreover we can find the solution in polynomial time by solving a linear program. This is a celebrated result (by Candes and Tao) that has created a whole new area called *Compressed sensing* . In this talk I will introduce the problem, and will prove a simple version of such reconstruction of sparse vectors from an under-determined system of linear equations.
(For everything that you want to know about compressed sensing, visit http://dsp.rice.edu/cs)
(For everything that you want to know about compressed sensing, visit http://dsp.rice.edu/cs)