Adaptive Least Mean Square (LMS) Algorithm with MATLAB Implementation
Adaptive Least Mean Square (LMS) algorithm implementation using MATLAB platform, including filter design and noise reduction applications
Adaptive Beamforming and Comparative Analysis of Different Beamforming Algorithms
Adaptive Beamforming Comparative Study of Adaptive Beamforming Algorithms Algorithms: Least Mean Squares (LMS), Recursive Least Squares (RLS), Conjugate Gradient Method, Kalman Filter-Based LMS Array Configurations: Linear Array, Rectangular Array
Implementation of Speech Enhancement
Custom GUI Interface for Speech Enhancement - Run the program by selecting "Run" from the "Debug" menu in main.c, featuring spectral subtraction, LMS adaptive filtering, and Wiener filter implementations for noise reduction.
Implementation of a Variable Step-Size Normalized Least Mean Square Adaptive Filtering Algorithm
This article presents the implementation of a variable step-size normalized least mean square (VSS-NLMS) adaptive filtering algorithm, including core mathematical derivations and computational procedures for autocorrelation matrix estimation and filter coefficient updates.
Smart Antenna Radiation Pattern - Beamforming Using Least Mean Square (LMS) Algorithm
Implementation of Smart Antenna Radiation Patterns with Beamforming Based on the Least Mean Square (LMS) Algorithm