Stochastic Modelling of the Set-Membership-sign-NLMS Algorithm

This paper proposes the Set-Membership sign-NLMS (SM-sign-NLMS) adaptive filter, which combines the ability for data censoring (offered by Set-Membership schemes) with robustness against impulsive noise (provided by signed schemes). The algorithm can present a much lower steady-state probability of...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access 2024-01, Vol.12, p.1-1
Hauptverfasser:	De Souza, Jose V. G., Henriques, Felipe da R., Siqueira, Newton N., Tarrataca, Luis, Andrade, Fabio A. A., Haddad, Diego B.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Adaptive Filtering Adaptive filters Algorithms Asymptotic properties Censorship Computational Complexity Cost function Data Censoring Data integrity Decoupling Fixed points (mathematics) Machine learning Markov processes Mathematical models Prediction algorithms Robustness Set-Membership Statistical analysis Steady-state Stochastic Models Stochastic processes Transient analysis Vectors
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!