Extension of ICA Algorithm with Reference Signals: Multi-Reference Fixed-Point Algorithm

In the source code section of my recent paper, I primarily extended the ICA algorithm with reference signals and proposed a multi-reference fixed-point algorithm for independent component analysis. This algorithmic extension aims to better address practical challenges and enhance the robustness of signal separation. By incorporating multiple reference signals, we achieve more accurate separation of mixed signals and obtain superior results. During the implementation of this extended algorithm, we employed a series of optimization strategies to improve computational efficiency and separation accuracy, including enhanced fixed-point iteration methods and optimized reference signal weighting schemes. We conducted extensive experimental validations, demonstrating the effectiveness and feasibility of this extended algorithm across various scenarios through MATLAB implementations featuring modular function designs for signal preprocessing, reference integration, and separation evaluation. Overall, this extended algorithm expands the applicability of ICA techniques and holds significant potential for both research and practical applications in signal processing domains.