Compressed sensing in multi-sensor architectures

My postdoc Il Yong Chun and I recently completed a new paper titled Compressed sensing and parallel acquisition.  In it we present a theoretical framework for the use of compressed sensing in multi-sensor systems.  These systems are found numerous applications, ranging from parallel MRI, to multi-view imaging and generalized sampling theory.  Our work provides a first mathematical analysis of the gains offered by parallel acquisition and compressed sensing, and presents new insight into questions of optimal sensor design.