Compressed sensing is a new area of signal processing. Its goal is to minimize the number of samples that need to be taken from a signal for faithful reconstruction. The performan...
The paper describes several efficient parallel implementations of the one-sided hyperbolic Jacobi-type algorithm for computing eigenvalues and eigenvectors of Hermitian matrices. ...
Sanja Singer, Sasa Singer, Vedran Novakovic, Davor...
—In this paper, we consider the amplified-and-forward relaying in a multichannel system with linear processing capability at the relay. We propose an analytical approach to stud...
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
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...