In this paper, we consider a low-complexity detection technique referred to as a reduced dimension maximum-likelihood search (RD-MLS). RD-MLS is based on a partitioned search which...
Jun Won Choi, Byonghyo Shim, Andrew C. Singer, Nam...
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
Three versions of a novel adaptive channel estimation approach, exploiting the over-sampled complex exponential basis expansion model (CE-BEM), is presented fordoubly selectivechan...
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
Abstract--In this paper, we deal with the problem of constrained code optimization for radar space-time adaptive processing (STAP) in the presence of colored Gaussian disturbance. ...
Antonio De Maio, Silvio De Nicola, Yongwei Huang, ...