MATLAB Source Code for LMS Filter with Variable Step Size Implementation

This MATLAB source code enables the implementation of LMS (Least Mean Squares) filter with variable step size simulation capabilities. The LMS filter is an adaptive filtering algorithm that automatically adjusts filter coefficients based on input signal characteristics to optimize signal processing. The MATLAB implementation involves key functions such as initializing filter weights, calculating the error signal, and updating coefficients using the LMS update rule: W(n+1) = W(n) + μ*e(n)*X(n), where μ represents the step size parameter. By modifying the step size parameter through code adjustments, users can control the filter's convergence rate and steady-state performance. The variable step size feature allows for dynamic adaptation where larger step sizes enable faster initial convergence while smaller values reduce steady-state error. The implementation includes simulation loops for processing input signals, real-time coefficient updates, and performance monitoring through mean squared error calculations. This MATLAB-based approach provides an efficient method for analyzing LMS filter behavior under different step size configurations and validating adaptive filtering theories through practical code execution.