What you can try:
1. Change the length of the training sequence: N.
2. Change equalizer order: eq_len.
3. Change the convergence multiplier: mu.
4. Try different signal model for system training
Andrey Kiselnikov (2021). LMS equalizer example (https://github.com/kiselnikov/lms_equalization_example), GitHub. Retrieved .
I run the example and understand each line in it but I have a question, in LMS the [MSE error vs itterations] graph is usually has instantaneous errors due to doesn't take into consideration the expectation in the adaptive equation, but on average it ends with almost zero error.
Why the is so clean like that ? why there are no fluctuations !
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