Analysis of Random Measurements: Lecture I

Roman Vershynin
University of California, Davis (UC Davis)

This is a mini-course in non-asymptotic theory of random matrices. It will give an introduction into the methods of modern probability theory and
geometric functional analysis.

Lecture 1. The sparse reconstruction problem and random matrices
a) The sparse reconstruction problem
b) Random matrices: asymptotic and non-asymptotic theories
c) The epsilon-net method

Audio (MP3 File, Podcast Ready) Presentation (PDF File) Additional Presentation Files (Zip Archive)

Back to Short Course: Sparse Representations and High Dimensional Geometry : In conjunction with the AMS 2007 Von Neumann Symposium