Explore MATLAB source code curated for "最小二乘法" with clean implementations, documentation, and examples.
MATLAB implementations of recursive system identification algorithms including basic RLS (Recursive Least Squares), extended RLS with forgetting factor, and RIV (Recursive Instrumental Variable) methods, all designed for 2nd-order systems with easy modification capability for different orders.
Implementation of RSSI-based localization algorithms using Maximum Likelihood Estimation (MLE) and Least Squares Method (LSM) approaches with detailed MATLAB code explanations and parameter optimization techniques
MATLAB program for modern spectral estimation using Singular Value Decomposition Total Least Squares method with comprehensive algorithmic implementation details.
Implementation of least squares matrix solution for overdetermined equations using MATLAB, featuring code explanations and algorithmic approaches.
Implementation of least squares method for curve fitting with MATLAB m-file containing simulation data and algorithm demonstration
The Robust Locally Weighted Regression algorithm, introduced by Cleveland[7], utilizes local observation data to perform polynomial-weighted fitting for target points and employs least squares estimation. This algorithm combines traditional local polynomial fitting, locally weighted regression, and a robust fitting procedure with strong resistance to outliers.
MATLAB implementation of least squares method covering node configuration, network setup, and algorithm validation for positioning systems
This code implementation demonstrates key channel estimation methods for OFDM systems, including Least Squares (LS), Linear Minimum Mean Square Error (LMMSE), and Low-Rank Minimum Mean Square Error approaches. The implementation features working MATLAB code with comprehensive algorithm explanations, suitable for beginners learning wireless communication systems. Download available for hands-on practice.
A MATLAB-based implementation of the Least Squares Method algorithm, compatible with MATLAB 7.01 and later versions, featuring comprehensive code documentation and practical application examples.
Graduation Project: Circle Fitting Program Implementing Least Squares Algorithm to Compute Center Coordinates and Radius