Explore MATLAB source code curated for "非参数估计" with clean implementations, documentation, and examples.
The Parzen Window method for kernel density estimation is straightforward to implement and particularly suitable for beginners learning non-parametric estimation techniques, with practical code examples for implementation.
Implementation of Parzen window non-parametric probability density function estimation for 2D datasets, featuring 3D visualization results. Includes complete documentation, program execution instructions, MATLAB source code, and graphical outputs. Developed as a pattern recognition assignment focusing on kernel density estimation techniques.
Mean Shift algorithm implementation for edge detection and image segmentation with code-related techniques
Kernel Density Estimation (KDE) Toolbox - A comprehensive implementation for non-parametric density estimation with support for multiple kernel functions and automatic bandwidth selection
MATLAB Implementation and Technical Explanation of Mean Shift Algorithm for Density-Based Clustering