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

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

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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 (2026). System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm (https://jp.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.

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バージョン 公開済み リリース ノート Action
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