Independent component analysis (ICA) is a data analysis tool that can be seen as a
refinement of principal component analysis or factor analysis. ICA recovers the structures in …

Second‐order source separation (SOS) is a data analysis tool which can be used for
revealing hidden structures in multivariate time series data or as a tool for dimension …

Blind source separation (BSS) is a well-known signal processing tool which is used to solve
practical data analysis problems in various fields of science. In BSS, we assume that the …

In independent component analysis it is assumed that the components of the observed
random vector are linear combinations of latent independent random variables, and the aim …

Abstract Independent Component Analysis (ICA) models are very popular semiparametric
models in which we observe independent copies of a random vector X=AS, where A is a non …

In graph signal processing (GSP), prior information on the dependencies in the signal is
collected in a graph which is then used when processing or analyzing the signal. Blind …

Further results on tests and a proof of Theorem 4.3. This supplement provides a simple
explicit expression for the proposed test statistics, derives local asymptotic powers of the …

Scatter matrices generalize the covariance matrix and are useful in many multivariate data
analysis methods, including well-known principal component analysis (PCA), which is …

In blind source separation, one assumes that the observed p time series are linear
combinations of p latent uncorrelated weakly stationary time series. To estimate the …

Recently a blind source separation model was suggested for spatial data, along with an
estimator based on the simultaneous diagonalization of two scatter matrices. The asymptotic …