Least Mean Square (LMS) Algorithm in Adaptive Equalization
Least Mean Square (LMS) algorithm is used to minimize the mean square error (MSE) between the desired equalizer output and the actual equalizer output.
Step 1: Initialize the weights with values 𝒆_𝟎.
Step 2: With this value, compute an approximation for the gradient of the MSE.
Step3:
We next compute an updated estimate of the weight vector e by adjusting weights in the direction of the negative gradient.
Where 𝝁 is a user defined parameter that determines convergence and residual error.
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