Explore MATLAB source code curated for "核函数" with clean implementations, documentation, and examples.
This implementation utilizes ant colony optimization for image edge detection, employing four distinct kernel functions for segmentation to generate comparative results and evaluate performance differences.
A comprehensive MATLAB toolkit featuring support vector machines and kernel functions with direct calling capabilities
Implementation and analysis of SVM kernel function selection and construction techniques in MATLAB environment, including built-in functions and custom kernel development approaches for optimal model performance.
Implementation of hybrid kernel functions by combining RBF and polynomial kernels within the libsvm framework, with comprehensive validation methodology
Gaussian filter kernel function generation algorithm that produces corresponding Gaussian kernels based on input parameter K with implementation details
Implementing edge extraction with wavelet transforms, comparing capabilities of various wavelet kernel functions, demonstrating the power of "mathematical microscope" through practical example: license plate localization.
PCA+Fisher methodology integrates kernel functions with principal component analysis and Fisher linear discriminant analysis for enhanced face recognition performance
Analyzing signal spectral information using bilinear time-frequency distributions, where designing different kernel functions enables various spectral effects and facilitates signal parameter analysis. Code implementation typically involves creating kernel matrices and applying convolution operations with signal autocorrelation functions.
Complete MATLAB implementation of Support Vector Machine (SVM) classifier including data preprocessing, model training, hyperparameter optimization, and performance evaluation
Detailed Code-Oriented Analysis of SVM-Based Text Classification Methodology