Explore MATLAB source code curated for "非负矩阵分解" with clean implementations, documentation, and examples.
This program implements a cutting-edge algorithm in matrix factorization: Non-Negative Matrix Factorization (NMF), featuring optimized computation methods for handling large-scale data while preserving non-negative constraints.
Implementation code from the seminal 1999 Nature paper introducing the fundamental non-negative matrix factorization algorithm
Nonnegative Matrix Factorization (NMF) – A Technique for Feature Extraction in Signals and Images, Also Applicable for Image Compression
Non-Negative Matrix Factorization (NMF) Implementation for Face Recognition with Functional Algorithm Source Code
Face feature extraction algorithm based on Non-negative Matrix Factorization (NMF), where the fundamental concept involves finding a linear subspace W such that all pixel values in the basis images constituting this subspace are positive, and the projection coefficients of face images onto this subspace are also non-negative.
A novel theory in blind source separation algorithms - Non-negative Matrix Factorization (NMF). The package includes implementation code with a graphical user interface (GUI) for practical applications.
Speech separation approach based on Non-negative Matrix Factorization (NMF), implemented in MATLAB with signal processing toolbox integration
Code implementation by international expert Serhat S. Bucak featuring incremental non-negative matrix factorization with practical examples and efficient functionality.
Comprehensive Materials for Implementing Non-negative Matrix Factorization Algorithm in MATLAB