Explore MATLAB source code curated for "学习曲线" with clean implementations, documentation, and examples.
Implementation of comparative simulation for learning curves between basic LMS algorithm and normalized LMS algorithm, including MATLAB code implementation details and performance analysis
1. This folder contains all programs for two experiments: classical power spectrum estimation and adaptive equalization algorithms. 2. R.m, LMS.m, and LMSmain.m are programs for adaptive equalization algorithms: R.m computes the autocorrelation matrix and eigenvalues of input signals; LMS.m implements the time-domain LMS algorithm using statistical methods to simulate learning curves under same channel parameters and different step sizes; LMSmain.m is the main experimental program that generates results and curves based on specific data requirements. 3. functionx.m, fzhouqitu.m, spectrum.m, bt.m, bart_lett.m, welch.m, and SPECTRUMmain.m are programs for classical spectrum estimation.
Simulation of LMS Adaptive Equalization in MATLAB Demonstrating Eigenvalue Spread and Step Size Parameter Learning Curves
This program focuses on studying the LMS adaptive algorithm, including convergence curve analysis, learning curve tracking, and average convergence trajectory evaluation with MATLAB/Python implementations.
MATLAB code implementation of LMS and RLS adaptive filtering algorithms with performance comparison
Adaptive Signal Processing - Least Mean Squares (LMS) Algorithm