Explore MATLAB source code curated for "最小二乘算法" with clean implementations, documentation, and examples.
Advanced plane fitting methodologies utilizing least squares optimization for 3D surface reconstruction, complete with flatness measurement and uncertainty quantification algorithms
Implementation of MSE calculation for least squares algorithm, minimum mean square error algorithm, and related approaches with MATLAB code examples
This program implements piecewise least squares algorithm for curve fitting, enabling segmented fitting of models to enhance accuracy and precision through data partition optimization.
A practical implementation case of the least squares algorithm with forgetting factor, including simulation models and M-files with detailed, easy-to-understand comments that demonstrate proper code structure and parameter configuration.
M-sequence signal algorithm simulation has broad application prospects in system identification. Compared with the multi-harmonic phase difference method, which requires prior knowledge of the number of identification parameters and complete cycle truncation for high precision, M-sequence signal testing imposes no such constraints. When identifying unknown models, the least squares algorithm can be utilized to observe the identification system's accuracy for determining model order. This algorithm not only provides computational methods for primitive polynomials used in M-sequence generation but also implements generation algorithms for M-sequence signals and develops corresponding identification methods.
MATLAB implementation of L1 Norm Least Squares algorithm for image reconstruction research, featuring high customizability and modifiable code structure.
MATLAB implementation of supervised feature selection and optimization based on least squares algorithm, including test datasets and comprehensive code documentation with technical specifications
Implementation of channel simulation combining least squares algorithm and decision feedback equalizer for optimizing channel performance, with code-level explanations of adaptive filtering and equalization techniques.