The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a
variety of emerging services and applications. However, the presence of rogue IoT devices …

This article reviews some key aspects of two important branches in unsupervised signal
processing: blind deconvolution and blind source separation (BSS). It also gives an …

Abstract Multi-criteria Decision Analysis (MCDA) is a methodology that has been classically
used to rank alternatives according to a set of decision criteria. The MCDA techniques have …

Abstract Information Theoretic Learning (ITL) methods have been applied in a variety of
applications as dynamic modeling, equalization and blind source separation. Usually, such …

Echo state networks (ESNs) can be interpreted as promoting an encouraging compromise
between two seemingly conflicting objectives:(i) simplicity of the resulting mathematical …

Datasets exist in real life in many formats (audio, music, image,...). In our case, we have
them from various sources mixed together. Our mixtures represent noisy audio data that …

Recently, many chaos-based communication systems have been proposed. They can
present the many interesting properties of spread spectrum modulations. Besides, they can …

We have addressed blind deconvolution in a multichannel framework. Recently, a robust
solution to this problem based on a Bayesian approach called sparse multichannel blind …

This paper revisits two prominent adaptive filtering algorithms, namely recursive least
squares (RLS) and equivariant adaptive source separation (EASI), through the lens of …

In the context of nonlinear Blind Source Separation (BSS), the Post-Nonlinear (PNL) model
is of great importance due to its suitability for practical nonlinear problems. Under certain …