System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm
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.
引用
Shujaat Khan (2024). System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm (https://www.mathworks.com/matlabcentral/fileexchange/63596-system-identification-using-least-mean-forth-lmf-and-least-mean-square-lms-algorithm), MATLAB Central File Exchange. に取得済み.
MATLAB リリースの互換性
プラットフォームの互換性
Windows macOS Linuxカテゴリ
タグ
謝辞
ヒントを得たファイル: Add white Uniform noise to a signal, System Identification Using Recursive Least Square (RLS) and Least Mean Square (LMS) algorithm
ヒントを与えたファイル: Variable Step-Size Least Mean Square (VSS-LMS) Algorithm
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!