Over the last ten years blind source separation (BSS) has become a prominent processing
tool in the study of human electroencephalography (EEG). Without relying on head modeling …

Edited by the people who were forerunners in creating the field, together with contributions
from 34 leading international experts, this handbook provides the definitive reference on …

In this article, we describe the role of time-frequency distributions (TFDs) in array processing.
We particularly focus on quadratic TFDs (QTFDs). We demonstrate how these distributions …

Matrix decompositions such as the eigenvalue decomposition (EVD) or the singular value
decomposition (SVD) have a long history in signal processing. They have been used in …

In an underdetermined mixture system with n unknown sources, it is a challenging task to
separate these sources from their m observed mixture signals, where mn By exploiting the …

A new algorithm for computing the nonorthogonal joint diagonalization of a set of matrices is
proposed for independent component analysis and blind source separation applications …

Bounded Component Analysis (BCA) is a recent approach which enables the separation of
both dependent and independent signals from their mixtures. In this approach, under the …

The multiple signal classification (MUSIC) algorithm based on spatial time-frequency
distribution (STFD) has been investigated for direction of arrival (DOA) estimation of closely …

Approximate methods have been considered as a means to the evaluation of discrete
transforms. In this work, we propose and analyze a class of integer transforms for the …

This paper introduces a new algorithm to approximate non-orthogonal joint diagonalization
(NOJD) of a set of complex matrices. This algorithm is based on the Frobenius norm …