In this paper we study the downlink of a hybrid analog-digital massive multi-user MIMO (MU-MIMO)
system. An efficient hybrid strategy is proposed, where the analog beamforming …

We address structured covariance estimation in elliptical distributions by assuming that the
covariance is a priori known to belong to a given convex set, eg, the set of Toeplitz or banded …

In this paper, we consider Tyler's robust covariance M-estimator under group symmetry
constraints. We assume that the covariance matrix is invariant to the conjugation action of a …

This paper describes the adaptive detection of point-like targets in a Gaussian environment
assuming a group symmetric structure for the interference covariance matrix. This special …

We study the Gaussian and robust covariance estimation, assuming the true covariance matrix
to be a Kronecker product of two lower dimensional square matrices. In both settings we …

A common assumption when sampling $p$-dimensional observations from $K$ distinct
group is the equality of the covariance matrices. In this paper, we propose two penalized $M$-…

This paper analyzes the performance of Tyler's M-estimator of the scatter matrix in elliptical
populations. We focus on the non-asymptotic setting and derive estimation error bounds …

Transformers have emerged as the underpinning architecture for Large Language Models (LLMs).
In generative language models, the inference process involves two primary phases: …

We consider the problem of generating symmetric pseudo-random sign (±1) matrices based
on the similarity of their spectra to Wigner's semicircular law. Using binary m-sequences (…

We consider the problem of generating pseudorandom matrices based on the similarity of
their spectra to Wigner's semicircular law. We introduce the notion of an r-independent pseudo…