Simulation Programs for Adaptive Filtering: LMS Algorithm and NLMS Algorithm
MATLAB Implementation of Adaptive Filtering Simulation Programs - LMS Algorithm and NLMS Algorithm with Code Descriptions
Adaptive Algorithm Employs NLMS Algorithm with Enhanced Code Implementation
1. The adaptive algorithm adopts the NLMS (Normalized Least Mean Square) algorithm from reference [2], providing faster convergence speed and reduced training iterations. Implementation typically involves calculating step size normalization using input signal power estimation. 2. Adaptive convergence step size has optimal values within (0, 2) range, with Lorenz sequence analysis determining 0.6 as the optimal parameter through empirical validation.
LMS Algorithm and Its Improved Variants in Adaptive Filtering
This analysis compares the core LMS algorithm with its improved variants including Normalized LMS (NLMS), Variable Step-Size LMS, and Transform-Domain LMS algorithms, examining their key differences and computational characteristics. It further extends the traditional LMS algorithm's applications and provides a comparative analysis with RLS algorithm properties, highlighting performance trade-offs in convergence speed and computational complexity.
LMS Algorithm and Its Improved Variants
This content provides a comparative analysis of the LMS algorithm and its enhanced versions (NLMS algorithm, variable step-size LMS algorithm, and transform-domain LMS algorithm), extending the application scope of traditional LMS algorithms through implementation-focused descriptions.
Speech Signal Separation Using NLMS Algorithm
This program employs the NLMS (Normalized Least Mean Squares) algorithm to separate dual-channel speech signals, utilizing an echo canceller mathematical model with enhanced processed speech output, demonstrating significant performance improvements.
Noise Adaptive Cancellation MATLAB Simulink Block with NLMS Algorithm
MATLAB Simulink block for noise adaptive cancellation implementing standard NLMS algorithm for noise cancellation, AEC (audio echo cancellation), and ANC (audio noise cancellation) applications
Performance Comparison of LMS and NLMS Algorithms
LMS_Identify.m implements a performance comparison between the LMS (Least Mean Squares) and NLMS (Normalized Least Mean Squares) adaptive filtering algorithms, including convergence analysis and MSE evaluation.