System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm

Version 1.2.0.0 (117 KB) von Shujaat Khan
System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm
5.0
(2)
530 Downloads
Aktualisiert 22. Feb 2018

Lizenz anzeigen

In this simulation least mean square (LMS) and least mean forth (LMF) algorithms are compared in non-Gaussian noisy environment for system identification task. Is it well known that the LMF algorithm outperforms the LMS algorithm in non-Gaussian environment, the same results can be seen in this implementation. Additionally a customized function for additive white uniform noise is also programmed.

Zitieren als

Shujaat Khan (2026). System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm (https://de.mathworks.com/matlabcentral/fileexchange/63596-system-identification-using-least-mean-forth-lmf-and-least-mean-square-lms-algorithm), MATLAB Central File Exchange. Abgerufen.

Kompatibilität der MATLAB-Version
Erstellt mit R2011a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux
Kategorien
Mehr zu Stair Plots finden Sie in Help Center und MATLAB Answers
Tags Tags hinzufügen
In neuem Tab öffnen
Version Veröffentlicht Versionshinweise
1.2.0.0

- Example
1.1.0.0

- Monte Carlo simulation setup
1.0.0.0

- Signal generator is generalized
- results on arbitrary system are shown