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 …

A Riemannian manifold optimization strategy is proposed to facilitate the relaxation of the
orthonormality constraint in a more natural way in the course of performing independent …

This work studies the problem of simultaneously separating and reconstructing signals from
compressively sensed linear mixtures. We assume that all source signals share a common …

Recent developments in quaternion-valued widely linear processing have established that
the exploitation of complete second-order statistics requires consideration of both the …

It is seemingly paradoxical to the classical definition of the independent component analysis
(ICA), that in reality, the true sources are often not strictly uncorrelated. With this in mind, this …

The strong uncorrelating transformation (SUT) is an effective tool for blind separation of
complex-valued independent sources, commonly applied to the (spatial) sample …

Matrix Joint Diagonalization (MJD) is a powerful approach for solving the Blind Source
Separation (BSS) problem. It relies on the construction of matrices which are diagonalized …

Let H denote the quaternion algebra. This paper investigates the generalized
complementary covariance, which is the ϕ-Hermitian quaternion matrix. We give the …

We develop an efficient algorithm for noncircular complex independent component analysis
(ICA) by optimizing the rows of separation matrix independently using a generalized …

在复值信号的盲分离算法中, 经常采用信号的峭度最大化作为代价函数. 以复数标准峭度代替
复数峭度, 将复数信号的标准峭度最大化作为新的代价函数, 采用修正的复值拟牛顿迭代算法对 …