System identification problems are always challenging to address in applications that
involve long impulse responses, especially in the framework of multichannel systems. In this …

Linear system identification is a key problem in many important applications, among which
echo cancelation is a very challenging one. Due to the long length impulse responses (ie …

The recursive least-squares (RLS) adaptive filter is an appealing choice in many system
identification problems. The main reason behind its popularity is its fast convergence rate …

Tensor-based signal processing methods are usually employed when dealing with
multidimensional data and/or systems with a large parameter space. In this paper, we …

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 …

Due to its fast convergence rate, the recursive least-squares (RLS) algorithm is very popular
in many applications of adaptive filtering, including system identification scenarios …

A number of Multiple Criteria Decision Analysis (MCDA) methods have been developed to
rank alternatives based on several decision criteria. Usually, MCDA methods deal with the …

Over the last two decades, tensor‐based methods have received growing attention in the
signal processing community. In this work, the authors proposed a comprehensive overview …

Abstract System identification problems are very difficult in the scenario of long length
impulse responses, raising challenges in terms of convergence, complexity, and accuracy of …

Tensors are multi-way arrays which can be used to model systems spanning many domains.
This work proposes to use tensors for characterizing, analyzing, and designing multi-domain …