Explore MATLAB source code curated for "PCA方法" with clean implementations, documentation, and examples.
Face Recognition System: Implementing Principal Component Analysis (PCA) to distinguish between human faces and non-face objects. Primarily developed for a stochastic processes course project, featuring dimensionality reduction and pattern classification techniques.
Implementation of handwritten digit recognition using PCA in MATLAB, involving preprocessing of raw images followed by digit recognition through traditional PCA, improved PCA algorithm, and 2D PCA methodology with code-focused explanations.
MATLAB program for subspace decomposition employing Principal Component Analysis (PCA) method with eigenvalue decomposition implementation
Implementation of PCA-based face recognition on ORL face database using singular value decomposition theorem, with nearest neighbor classifier for image classification
Five comprehensive PCA-based fault diagnosis routines for industrial systems, including Kernel PCA (KPCA) implementation. These well-documented MATLAB routines feature detailed code annotations, algorithm explanations, and practical examples for industrial fault detection using principal component analysis methodologies.