Nonlinear blind identification with three-dimensional tensor analysis
type: Item
instance of: scholarly article
title: Nonlinear blind identification with three-dimensional tensor analysis
zbMATH Open document ID: 1264.93252
DOI: 10.1155/2012/284815
author: Imen Cherif
author: Sabeur Abid
author: Farhat Fnaiech
published in: Mathematical Problems in Engineering
publication date: 2013-06-11T00:00:00Z
review text: Summary: This paper deals with the analysis of a third-order tensor composed of a fourth-order output cumulants used for blind identification of a second-order Volterra-Hammerstein series. It is demonstrated that this nonlinear identification problem can be converted in a multivariable system with multiequations having the form of \(Ax + By = c\). The system may be solved using several methods. Simulation results with the Iterative Alternating Least Squares (IALS) algorithm provide good performances for different signal-to-noise ratio (SNR) levels. Convergence issues using the reversibility analysis of matrices \(A\) and \(B\) are addressed. Comparison results with other existing algorithms are carried out to show the efficiency of the proposed algorithm.
Mathematics Subject Classification ID: 93E12
zbMATH DE Number: 6173155
Wikidata QID: Q58911380
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/284815
OpenAlex ID: W2040369029
cites work: Solving linear coupled fractional differential equations by direct operational method and some applications
cites work: Markov models for image labeling
cites work: Specific mathematical aspects of dynamics generated by coherence functions
cites work: Blind identification of Volterra-Hammerstein systems
cites work: Nonlinear system modeling and identification using Volterra‐PARAFAC models
cites work: Blind identification of second-order Hammerstein series
cites work: Q5689624
description: scientific article; zbMATH DE number 6173155