Fall 2011 – Page 2

Restricted Isometry Constants in Compressed Sensing | Network localization with some new wrinkles: Noncovex geometry in low dimension

Bubacarr’s talk: ABSTRACT: Restricted Isometry Constants (RICs) of a matrix are a popular tool in the analysis of compressed sensing algorithms. The best known bounds will be presented for Gaussian matrices as well as expander graphs. In the former case we will also present explicit formulae for the bounds in …

An optimal architecture for poset-causal systems | Computable Bounds on Sparsity Recovery

Gongguo’s talk: Title: Computable Bounds on Sparsity Recovery Abstract: The performance of sparsity recovery depends on the structures of the sensing matrices. The quality of these matrices in the context of signal recovery is usually quantified by the restricted isometry constant and its variants. However, the restricted isometry constant and …