Tensor-based adaptive filtering algorithms

LM Dogariu, CL Stanciu, C Elisei-Iliescu, C Paleologu… - Symmetry, 2021 - mdpi.com
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 …

Noise reduction and speech enhancement using wiener filter

HH Nuha, AA Absa - … Conference on Data Science and Its …, 2022 - ieeexplore.ieee.org
Digital data transmission rate may reach over 2.5 Tb/s using the orthogonal frequency
division multiplexing (OFDM). Digital speech enhancement is crucial during the pandemic …

Low-complexity recursive least-squares adaptive algorithm based on tensorial forms

ID Fîciu, CL Stanciu, C Anghel, C Elisei-Iliescu - Applied Sciences, 2021 - mdpi.com
Modern solutions for system identification problems employ multilinear forms, which are
based on multiple-order tensor decomposition (of rank one). Recently, such a solution was …

Efficient functional link adaptive filters based on nearest Kronecker product decomposition

A Nezamdoust, M Huemer, A Uncini… - ICASSP 2024-2024 …, 2024 - ieeexplore.ieee.org
Functional link adaptive filters (FLAFs) utilize expansion blocks to nonlinearly augment the
input signal to a higher dimensional space, after which an adaptive weight algorithm is …

LMS algorithms for multilinear forms

LM Dogariu, C Paleologu, J Benesty… - … on Electronics and …, 2020 - ieeexplore.ieee.org
Solving a high-dimension system identification problem could involve significant challenges
in terms of complexity and accuracy of the solution. Due to the large parameter space, a …

A Kalman filter for multilinear forms and its connection with tensorial adaptive filters

LM Dogariu, C Paleologu, J Benesty, CL Stanciu… - Sensors, 2021 - mdpi.com
The Kalman filter represents a very popular signal processing tool, with a wide range of
applications within many fields. Following a Bayesian framework, the Kalman filter …

Tensor-based recursive least-squares adaptive algorithms with low-complexity and high robustness features

ID Fîciu, CL Stanciu, C Elisei-Iliescu, C Anghel - Electronics, 2022 - mdpi.com
The recently proposed tensor-based recursive least-squares dichotomous coordinate
descent algorithm, namely RLS-DCD-T, was designed for the identification of multilinear …

[PDF][PDF] Intelligent Fine-Grained Daily Living Locomotion Prediction Based on Skeleton Modeling and CNN.

M Javeed, N Al Mudawi, A Alazeb, H Aljuaid… - Traitement du …, 2024 - researchgate.net
Activities of daily living are important for human locomotion prediction. Humans perform
several activities while moving from one place to another. Some of these activities are …

Identification of Multilinear Systems: A Brief Overview

LM Dogariu, C Paleologu, J Benesty… - Advances in Principal …, 2022 - books.google.com
Nonlinear systems have been studied for a long time and have applications in numerous
research fields. However, there is currently no global solution for nonlinear system …

Improving the Accuracy of Systems for Measuring the Angular Position of Moving Objects with an Adaptive Wiener Filter

D Dichev, I Zhelezarov, B Georgiev… - 2024 XXXIV …, 2024 - ieeexplore.ieee.org
This paper presents a method for increasing the accuracy of systems for measuring the
angular position of moving objects by using an adaptive Wiener filter. In the context of …