Sampling and reconstruction in the 21st century

Abstract

We review advances in sampling theory since the turn of the century, with a special emphasis on how basis decompositions have allowed us to pose and analyze sampling problems more through the lens of linear algebra, than through the traditional lens of filtering and Fourier decompositions. This new framework also allows us to incorporate nonlinear (sparse) signal models into the signal reconstruction process using optimization.