Independent Component Analysis
MATLAB Independent Component Analysis with functions including fastica, icaplot, remmean, and whiten for blind source separation, mean removal, and whitening preprocessing
FastICA Fixed-Point Algorithm Package
FastICA fixed-point algorithm package including raw image data and corresponding MATLAB implementation, serving as a valuable learning resource for independent component analysis (ICA) researchers.
FastICA Algorithm Implementation with MATLAB Documentation
(MATLAB: Includes complete usage documentation and code examples)
Speech Separation using FastICA
Classic implementation of FastICA for speech separation in MATLAB
FastICA: The Most Classic Fixed-Point Algorithm in Blind Source Separation
FastICA, the most classical fixed-point algorithm in blind source separation, offers a straightforward implementation suitable for beginners, with core operations including whitening, non-Gaussianity maximization via contrast functions, and Newton-Raphson iteration.
Color Image Inpainting Using Dictionary Learning with FastICA Algorithm
Color Image Restoration via Learning Dictionary Approach with FastICA-Based Dictionary Learning Methodology
Whitening Algorithm Implementation in fastICA
The whitening algorithm serves as a crucial preprocessing step in fastICA, involving data normalization through eigenvalue decomposition and covariance matrix calculations.
MATLAB Implementation of FastICA Algorithm for Blind Source Separation
Complete MATLAB implementation of the FastICA algorithm with full source code. This package provides a comprehensive blind source separation tool using Independent Component Analysis (ICA), featuring detailed algorithm explanations and ready-to-use code examples for signal processing applications.
FASTICA-Based Speech Signal Separation MATLAB Source Code
MATLAB source code implementation of FASTICA algorithm for speech signal separation, featuring independent component analysis (ICA) with optimized convergence and signal processing capabilities.
FastICA Rapid Independent Component Analysis with MATLAB Implementation
Comprehensive MATLAB source code for FastICA algorithm featuring an intuitive graphical user interface (GUI) for easy operation. Capable of processing multi-channel mixed signals, outputting computational results, and generating signal visualization graphs for enhanced analysis. Includes implementation details for signal preprocessing, whitening transformation, and iterative component separation using fixed-point algorithm.