A Recursive Least-Squares Algorithm for the Identification of Trilinear Forms

Autor:	Camelia Elisei-Iliescu, Laura-Maria Dogariu, Constantin Paleologu, Jacob Benesty, Andrei-Alexandru Enescu, Silviu Ciochină
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	adaptive filters recursive least-squares (RLS) algorithm system identification tensor decomposition trilinear forms Industrial engineering. Management engineering T55.4-60.8 Electronic computers. Computer science QA75.5-76.95
Zdroj:	Algorithms, Vol 13, Iss 6, p 135 (2020)
Druh dokumentu:	article
ISSN:	1999-4893
DOI:	10.3390/a13060135
Popis:	High-dimensional system identification problems can be efficiently addressed based on tensor decompositions and modelling. In this paper, we design a recursive least-squares (RLS) algorithm tailored for the identification of trilinear forms, namely RLS-TF. In our framework, the trilinear form is related to the decomposition of a third-order tensor (of rank one). The proposed RLS-TF algorithm acts on the individual components of the global impulse response, thus being efficient in terms of both performance and complexity. Simulation results indicate that the proposed solution outperforms the conventional RLS algorithm (which handles only the global impulse response), but also the previously developed trilinear counterparts based on the least-mean- squares algorithm.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/cd52dd4e61344ea9af2807e74ce7037a Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.