Multiple Functions for EEG Independent Component Analysis

Multiple specialized functions are available for conducting EEG independent Component Analysis (ICA). These functions enable comprehensive analysis outcomes through advanced signal processing techniques, including frequency domain analysis using FFT implementations, amplitude quantification via peak detection algorithms, and phase analysis through Hilbert transform methods. The toolkit also incorporates event-related potential (ERP) extraction capabilities using epoch-based averaging techniques. Implementation requires minimal coding expertise - users can directly invoke pre-configured functions with standardized EEG data inputs without additional data preprocessing or custom programming. The modular design employs efficient matrix operations optimized for large-scale electrophysiological datasets, utilizing parallel processing where applicable. These functions serve as robust analytical tools for EEG research, facilitating rapid generation of high-quality results through automated processing pipelines and validated ICA decomposition algorithms.