MATLAB Implementation of FastICA Algorithm for Blind Source Separation

The FastICA algorithm for Independent Component Analysis is an efficient implementation that accelerates convergence compared to traditional ICA methods, significantly improving analysis efficiency. This MATLAB implementation includes a comprehensive graphical user interface (GUI) that simplifies parameter configuration and result visualization. Key algorithmic features include whitening preprocessing, symmetric orthogonalization, and fixed-point iteration with configurable nonlinearity functions. The code structure handles signal preprocessing, component estimation, and result validation through built-in visualization tools. Users can perform blind source separation on mixed signals through intuitive GUI controls while accessing advanced parameters for custom convergence criteria and component count specification. This makes FastICA an essential tool in signal processing applications, enhancing both workflow efficiency and analytical accuracy through optimized numerical computation and interactive result exploration.