Written by the leading expert in the field, this text reviews the major new developments in
envelope models and methods An Introduction to Envelopes provides an overview of the …

One of the main vulnerabilities of GNSS receivers is their exposure to intentional or
unintentional jamming signals, which could even cause service unavailability. Several …

This paper provides a unified view of, and a further insight into, a class of optimal reduced-
rank estimators and filters. An alternating power (AP) method for computing the optimal …

This book organizes principles and methods of signal processing and machine learning into
the framework of coherence. The book contains a wealth of classical and modern methods …

Recently, state-space subspace system identification (4SID) has been suggested as an
alternative to the more traditional prediction error system identification. The aim of this paper …

The low-rank approximation problem is to approximate optimally, with respect to some norm,
a matrix by one of the same dimension but smaller rank. It is known that under the Frobenius …

Hyperspectral endmember extraction is a process to estimate endmember signatures from
the hyperspectral observations, in an attempt to study the underlying mineral composition of …

The standard vector autoregressive (VAR) models suffer from overparameterization which is
a serious issue for high-dimensional time series data as it restricts the number of variables …

Generalized multivariate analysis of variance (GMANOVA) and related reduced-rank
regression are general statistical models that comprise versions of regression, canonical …

In the regression model $\mathbf {Y}=\eta+\mathbf {BX}+\mathbf {Z} $ with $\mathbf {Z} $
unobserved, $\mathscr {E}\mathbf {Z}=\mathbf {0} $ and $\mathscr {E}\mathbf {ZZ}'=\mathbf …