System Identification Using Least Mean Forth (LMF) and Least Mean Square (LMS) algorithm
Updated Thu, 22 Feb 2018 04:18:42 +0000
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.
Shujaat Khan (2023). 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. Retrieved .
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Inspired by: Add white Uniform noise to a signal, System Identification Using Recursive Least Square (RLS) and Least Mean Square (LMS) algorithm
Inspired: Variable Step-Size Least Mean Square (VSS-LMS) Algorithm
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