Improved LMS Algorithm - Normalized LMS Algorithm

This program introduces an improved version of the LMS algorithm - the normalized LMS algorithm. Building upon the traditional LMS foundation, the normalized LMS algorithm demonstrates enhanced convergence performance through adaptive step size normalization. The implementation features comparative visualization plots that clearly illustrate the performance differences between the two algorithms. The comparison graphs reveal that the normalized LMS algorithm achieves faster convergence and smaller steady-state error compared to its traditional counterpart. Key implementation aspects include: step size normalization based on input signal power, recursive error computation, and weight update mechanisms that automatically adjust to signal conditions. This improved performance makes the normalized LMS algorithm particularly advantageous for real-world applications where rapid adaptation and minimized error are critical requirements. The algorithm's efficient MATLAB implementation utilizes vectorized operations for optimal computational performance, featuring functions for signal processing, error tracking, and real-time parameter adaptation.