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.
Cite As
Shujaat Khan (2026). System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm (https://nl.mathworks.com/matlabcentral/fileexchange/63596-system-identification-using-least-mean-forth-lmf-and-least-mean-square-lms-algorithm), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.2.0.0 (117 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
