We examine the application of current research in sparse signal recovery to the problem of channel estimation. Specifically, using an Orthogonal Frequency Division Multiplexed (O...
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
Abstract-- The FOCal Underdetermined System Solver (FOCUSS) algorithm has already found many applications in signal processing and data analysis, whereas the regularized MFOCUSS al...
In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is unknown. Assuming just that...