In various disciplines, information about the same phenomenon can be acquired from
different types of detectors, at different conditions, in multiple experiments or subjects …

Starting with a simple generative model and the assumption of statistical independence of
the underlying components, independent component analysis (ICA) decomposes a given …

The deviation of continuous and discrete complex random variables from the traditional
proper and symmetric assumption to a generalized improper and asymmetric …

Fusion of information from multiple sets of data in order to extract a set of features that are
most useful and relevant for the given task is inherent to many problems we deal with today …

Complex-valued signals occur in many areas of science and engineering and are thus of
fundamental interest. When developing signal processing methods in the complex domain …

Signal separation and extraction are important tasks for devices recording audio signals in
real environments which, aside from the desired sources, often contain several interfering …

By assuming latent sources are statistically independent, independent component analysis
(ICA) separates underlying sources from a given linear mixture. Since in many applications …

In many daily-life scenarios, acoustic sources recorded in an enclosure can only be
observed with other interfering sources. Hence, convolutive Blind Source Separation (BSS) …

This paper deals with the problem of joint complex matrix diagonalization by considering
both the Hermitian and transpose congruences. We address the general case where the …

This paper first establishes a new complex independent component analysis (cICA)
algorithm based on the spatiotemporal extension of complex‐valued entropy bound …