On the effect of filter variability in compressive sensing systems

摘要

In this paper, we study the effect of filter variability in compressive sensing systems. Compressive sensing entails projecting the signal on a set of random signals, which is done by means of mixers and low pass filters. When reconstructing the signal, it is important to have a model for the sensing hardware, hence, the need to mitigate variability effects on the reconstruction process. In order to do that, there is a need for quantifying the effect of variability on reconstruction in order to be able to design compressive sensing systems that are robust to variability.