Explore MATLAB source code curated for "PCA" with clean implementations, documentation, and examples.
MATLAB source code implementations for PCA and ICA - two classical feature extraction methods widely used in image processing, featuring dimensionality reduction and signal separation capabilities
This algorithm implements Independent Component Analysis (ICA) and Principal Component Analysis (PCA) for process monitoring and fault diagnosis, including automated data structure adaptation for enhanced stability and reliability.
Face Recognition with PCA Analysis in MATLAB - Fully Commented Code Implementation
MATLAB implementation example of PCA-based face recognition system with code demonstration.
PCA MATLAB program algorithm with experimental validation, providing useful dimensionality reduction implementation for data processing applications
Implementing Image Clustering by Combining PCA and Fuzzy C-Means Algorithms
Robust Sparse PCA algorithm demonstrating strong resistance to noise and outlier data with enhanced implementation features
A comprehensive MATLAB assignment implementing various image fusion algorithms including IHS, PCA, weighted average, pyramid-based, and wavelet fusion methods with detailed code descriptions.
MATLAB implementation of Principal Component Analysis (PCA)-based Elman and RBF neural networks featuring optimized computational efficiency and straightforward code structure
Implementing Principal Component Analysis (PCA) in MATLAB to calculate and visualize image projections onto the first, second, and third principal components. This tutorial covers the complete workflow from image preprocessing to projection reconstruction with code implementation details.