MATLAB Implementation of Independent Component Analysis (ICA) with Complete Source Code

This is a complete ICA source code implementation that we hope will be beneficial to users. Let me share important details about this source code. First, it is an open-source project, meaning anyone can freely use, modify, and distribute it. The code demonstrates core ICA algorithms including signal preprocessing, whitening transformation, and iterative optimization using methods like FastICA or JADE for blind source separation. Second, the source code offers high extensibility, allowing customization and enhancement for different requirements through modular functions for data processing, convergence testing, and component visualization. Additionally, it includes valuable features and modules such as data normalization routines, covariance matrix computation, and eigenvalue decomposition for dimension reduction. The implementation also contains performance evaluation metrics for assessing separation quality. In summary, this ICA source code serves as a valuable resource that benefits both beginners learning signal processing techniques and professionals developing advanced separation algorithms, with clear documentation on parameter tuning and algorithm selection.