In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse an...
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
We propose a new method named compressive structured light for recovering inhomogeneous participating media. Whereas conventional structured light methods emit coded light patterns...
Jinwei Gu, Shree K. Nayar, Eitan Grinspun, Peter N...
—This paper addresses the problem of simultaneous signal recovery and dictionary learning based on compressive measurements. Multiple signals are analyzed jointly, with multiple ...
Jorge Silva, Minhua Chen, Yonina C. Eldar, Guiller...