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 (2020). 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 .
When I use the Algorithm in a complex system where the input and the output are complex. I didn't get the expected results/curves. Does the command need to be modified adapted to the complex values?
Sir can you please suggest some papers on blind system identification in time varying system
Thank you @jing zhang and @Rui Yang
- Monte Carlo simulation setup
- Signal generator is generalized