This book provides an excellent reference for all professionals working in the area of array
signal processing and its applications in wireless communications. Wideband beamforming …

Independent component analysis (ICA) aims at decomposing an observed random vector
into statistically independent variables. Deflation-based implementations, such as the …

We present a set of statistical methods for the analysis of DNA methylation microarray data,
which account for tumor purity. These methods are an extension of our previously developed …

We revise the problem of extracting one independent component from an instantaneous
linear mixture of signals. The mixing matrix is parameterized by two vectors: one column of …

This study presents a blind and geometric technique which pursues the linear
decomposition of the observations in bounded component signals. The bounded component …

In many applications extraction of source signals of interest from observed signals is a more
feasible approach than simultaneous separation of all the source signals, since the latter …

In this paper, we address the problem of extracting all super-Gaussian source signals from a
linear mixture in which (i) the number of super-Gaussian sources K is less than that of …

We address the convolutive blind source separation problem for the (over-) determined case
where (i) the number of nonstationary target-sources K is less than that of microphones M …

We propose fast independent vector extraction (FIVE), a new algorithm that blindly extracts a
single non-Gaussian source from a Gaussian background. The algorithm iteratively …

In this paper, we use a two-stage sparse factorization approach for blindly estimating the
channel parameters and then estimating source components for electroencephalogram …