Abstract: The null space property and the restricted isometry property for a measurement matrix are two basic properties in compressive sampling, and are closely related to the sparse approximation. In this talk, we introduce the sparse approximation property for a measurement matrix, a weaker version of the restricted isometry property and a stronger version of the null space property. We show that the sparse approximation property for a measurement matrix could be an appropriate condition to consider stable recovery of any compressible signal from its noisy measurements.
2-4pm, 01/19/2011 in Duncan Hall 3076